The internet of things (IoT) is a revolutionary innovation in many aspects of our society including interactions, financial activity, and global security such as the military and battlefield internet. Due to the limited energy and processing capacity of network devices, security, energy consumption, compatibility, and device heterogeneity are the long-term IoT problems. As a result, energy and security are critical for data transmission across edge and IoT networks. Existing IoT interoperability techniques need more computation time, have unreliable authentication mechanisms that break easily, lose data easily, and have low confidentiality. In this paper, a key agreement protocol-based authentication mechanism for IoT devices is offered as a solution to this issue. This system makes use of information exchange, which must be secured to prevent access by unauthorized users. Using a compact contiki/cooja simulator, the performance and design of the suggested framework are validated. The simulation findings are evaluated based on detection of malicious nodes after 60 minutes of simulation. The suggested trust method, which is based on privacy access control, reduced packet loss ratio to 0.32%, consumed 0.39% power, and had the greatest average residual energy of 0.99 mJoules at 10 nodes.
An efficient security framework for intrusion detection and prevention in int...IJECEIAES
Over the past few years, the internet of things (IoT) has advanced to connect billions of smart devices to improve quality of life. However, anomalies or malicious intrusions pose several security loopholes, leading to performance degradation and threat to data security in IoT operations. Thereby, IoT security systems must keep an eye on and restrict unwanted events from occurring in the IoT network. Recently, various technical solutions based on machine learning (ML) models have been derived towards identifying and restricting unwanted events in IoT. However, most ML-based approaches are prone to miss-classification due to inappropriate feature selection. Additionally, most ML approaches applied to intrusion detection and prevention consider supervised learning, which requires a large amount of labeled data to be trained. Consequently, such complex datasets are impossible to source in a large network like IoT. To address this problem, this proposed study introduces an efficient learning mechanism to strengthen the IoT security aspects. The proposed algorithm incorporates supervised and unsupervised approaches to improve the learning models for intrusion detection and mitigation. Compared with the related works, the experimental outcome shows that the model performs well in a benchmark dataset. It accomplishes an improved detection accuracy of approximately 99.21%.
Efficient network management and security in 5G enabled internet of things us...IJECEIAES
The rise of fifth generation (5G) networks and the proliferation of internet- of-things (IoT) devices have created new opportunities for innovation and increased connectivity. However, this growth has also brought forth several challenges related to network management and security. Based on the review of literature it has been identified that majority of existing research work are limited to either addressing the network management issue or security concerns. In this paper, the proposed work has presented an integrated framework to address both network management and security concerns in 5G internet-of-things (IoT) network using a deep learning algorithm. Firstly, a joint approach of attention mechanism and long short-term memory (LSTM) model is proposed to forecast network traffic and optimization of network resources in a, service-based and user-oriented manner. The second contribution is development of reliable network attack detection system using autoencoder mechanism. Finally, a contextual model of 5G-IoT is discussed to demonstrate the scope of the proposed models quantifying the network behavior to drive predictive decision making in network resources and attack detection with performance guarantees. The experiments are conducted with respect to various statistical error analysis and other performance indicators to assess prediction capability of both traffic forecasting and attack detection model.
A signature-based data security and authentication framework for internet of...IJECEIAES
This document presents a research paper that proposes a signature-based data security and authentication framework for Internet of Things (IoT) applications. The paper introduces a novel computational model that establishes a unique authentication process using a simplified encryption strategy. The model considers both local and global IoT environments and implements an authentication mechanism using challenge-response exchanges between communicating nodes. A digital signature is generated using parameters like random seeds, secret keys, prime values, and data packets. Simulation results show that the proposed system offers efficient security and data transmission performance in the presence of unknown adversaries, performing better than commonly used security solutions in vulnerable IoT environments.
Privacy-aware secured discrete framework in wireless sensor networkIJECEIAES
Rapid expansion of wireless sensor network-internet of things (WSN-IoT) in terms of application and technologies has led to wide research considering efficiency and security aspects. Considering the efficiency approach such as data aggregation along with consensus mechanism has been one of the efficient and secure approaches, however, privacy has been one of major concern and it remains an open issue due to low classification and high misclassification rate. This research work presents the privacy and reliable aware discrete (PRD-aggregation) framework to protect and secure the privacy of the node. It works by initializing the particular variable for each node and defining the threshold; further nodes update their state through the functions, and later consensus is developed among the sensor nodes, which further updates. The novelty of PRD is discretized transmission for efficiency and security. PRD-aggregation offers reliability through efficient termination criteria and avoidance of transmission failure. PRD-aggregation framework is evaluated considering the number of deceptive nodes for securing the node in the network. Furthermore, comparative analysis proves the marginal improvisation in terms of discussed parameter against the existing protocol.
AN EFFICIENT SECURE CRYPTOGRAPHY SCHEME FOR NEW ML-BASED RPL ROUTING PROTOCOL...IJNSA Journal
Internet of Things (IoT) offers reliable and seamless communication for the heterogeneous dynamic lowpower and lossy network (LLNs). To perform effective routing in IoT communication, LLN Routing Protocol (RPL) is developed for the tiny nodes to establish connection by using deflaut objective functions: OF0, MRHOF, for which resources are constraints like battery power, computation capacity, memory communication link impacts on varying traffic scenarios in terms of QoS metrics like packet delivery ratio, delay, secure communication channel. At present, conventional Internet of Things (IoT) are having secure communication channels issue for transmission of data between nodes. To withstand those issues, it is necessary to balance resource constraints of nodes in the network. In this paper, we developed a security algorithm for IoT networks with RPL routing. Initially, the constructed network in corporates optimizationbased deep learning (reinforcement learning) for route establishment in IoT. Upon the establishment of the route, the ClonQlearn based security algorithm is implemented for improving security which is based onaECC scheme for encryption and decryption of data. The proposed security technique incorporates reinforcement learning-based ClonQlearnintegrated with ECC (ClonQlearn+ECC) for random key generation. The proposed ClonQlearn+ECCexhibits secure data transmission with improved network performance when compared with the earlier works in simulation. The performance of network expressed that the proposed ClonQlearn+ECC increased the PDR of approximately 8% - 10%, throughput of 7% - 13%, end-to-end delay of 5% - 10% and power consumption variation of 3% - 7%.
Survey on Optimization of IoT Routing Based On Machine Learning TechniquesIRJET Journal
This document discusses several studies on using machine learning techniques to optimize routing in Internet of Things (IoT) networks. It first provides background on IoT and challenges with routing in IoT networks due to factors like device mobility and limited resources. It then summarizes several papers that propose different machine learning approaches for IoT routing, including using reinforcement learning to balance node loads and extend network lifetime, integrating deep reinforcement learning into existing routing protocols to improve performance, and using Q-learning at each node to learn optimal parent selection policies based on network conditions. Finally, it discusses a study that developed an energy-efficient routing algorithm for wireless sensor networks based on dynamic programming to maximize network lifetime.
A data quarantine model to secure data in edge computingIJECEIAES
Edge computing provides an agile data processing platform for latencysensitive and communication-intensive applications through a decentralized cloud and geographically distributed edge nodes. Gaining centralized control over the edge nodes can be challenging due to security issues and threats. Among several security issues, data integrity attacks can lead to inconsistent data and intrude edge data analytics. Further intensification of the attack makes it challenging to mitigate and identify the root cause. Therefore, this paper proposes a new concept of data quarantine model to mitigate data integrity attacks by quarantining intruders. The efficient security solutions in cloud, ad-hoc networks, and computer systems using quarantine have motivated adopting it in edge computing. The data acquisition edge nodes identify the intruders and quarantine all the suspected devices through dimensionality reduction. During quarantine, the proposed concept builds the reputation scores to determine the falsely identified legitimate devices and sanitize their affected data to regain data integrity. As a preliminary investigation, this work identifies an appropriate machine learning method, linear discriminant analysis (LDA), for dimensionality reduction. The LDA results in 72.83% quarantine accuracy and 0.9 seconds training time, which is efficient than other state-of-the-art methods. In future, this would be implemented and validated with ground truth data.
An efficient approach for secured communication in wireless sensor networks IJECEIAES
Wireless sensor network (WSN) have limited bandwidth, low computational functions, energy constraints. Inspite of these constraints, WSN is useful where communication happens without infrastructure support. The main concern of WSN is the security as the sensor nodes may be attacked and information may be hacked. Security of WSN should have the capability to ensure that the message received was sent by the particular sent node and not modified during transmission. WSN applications require lightweight and strong authentication mechanisms for obtaining data from unprivileged users. In wireless sensor networks, authentication is the effective method to stop unauthorized and undisrupted communication service. In order to strengthen the authenticated communication, several researchers have developed mechanisms. Some of the techniques work with identifying the attacked node or detecting injected bogus message in the network. Encryption and decryption are the popular methods of providing the security. These are based on either public-key or symmetric-key cryptosystems.Many of the existing solutions have limitations in communication and computational expertise. Also, the existing mechanisms lack in providing strength and scalability of the network. In order address these issues; a polynomial based method was introduced in recent days. Key distribution is a significant aspect in key management in WSNs. The simplest method of distribution of key is by hand which was used in the days of couriers. Now a day, most distribution of keys is done automatically. The automatic distribution of keys is essential and convenient in networks that require two parties to transmit their security keys in the same communication medium. In this work, a new type of key exchange mechanism is proposed. The proposed method for authentication among sensor nodes proves to be promising as per the simulation results. The nodes which are unknown to each other setup a private however arbitrary key for the symmetric key cryptosystem.
An efficient security framework for intrusion detection and prevention in int...IJECEIAES
Over the past few years, the internet of things (IoT) has advanced to connect billions of smart devices to improve quality of life. However, anomalies or malicious intrusions pose several security loopholes, leading to performance degradation and threat to data security in IoT operations. Thereby, IoT security systems must keep an eye on and restrict unwanted events from occurring in the IoT network. Recently, various technical solutions based on machine learning (ML) models have been derived towards identifying and restricting unwanted events in IoT. However, most ML-based approaches are prone to miss-classification due to inappropriate feature selection. Additionally, most ML approaches applied to intrusion detection and prevention consider supervised learning, which requires a large amount of labeled data to be trained. Consequently, such complex datasets are impossible to source in a large network like IoT. To address this problem, this proposed study introduces an efficient learning mechanism to strengthen the IoT security aspects. The proposed algorithm incorporates supervised and unsupervised approaches to improve the learning models for intrusion detection and mitigation. Compared with the related works, the experimental outcome shows that the model performs well in a benchmark dataset. It accomplishes an improved detection accuracy of approximately 99.21%.
Efficient network management and security in 5G enabled internet of things us...IJECEIAES
The rise of fifth generation (5G) networks and the proliferation of internet- of-things (IoT) devices have created new opportunities for innovation and increased connectivity. However, this growth has also brought forth several challenges related to network management and security. Based on the review of literature it has been identified that majority of existing research work are limited to either addressing the network management issue or security concerns. In this paper, the proposed work has presented an integrated framework to address both network management and security concerns in 5G internet-of-things (IoT) network using a deep learning algorithm. Firstly, a joint approach of attention mechanism and long short-term memory (LSTM) model is proposed to forecast network traffic and optimization of network resources in a, service-based and user-oriented manner. The second contribution is development of reliable network attack detection system using autoencoder mechanism. Finally, a contextual model of 5G-IoT is discussed to demonstrate the scope of the proposed models quantifying the network behavior to drive predictive decision making in network resources and attack detection with performance guarantees. The experiments are conducted with respect to various statistical error analysis and other performance indicators to assess prediction capability of both traffic forecasting and attack detection model.
A signature-based data security and authentication framework for internet of...IJECEIAES
This document presents a research paper that proposes a signature-based data security and authentication framework for Internet of Things (IoT) applications. The paper introduces a novel computational model that establishes a unique authentication process using a simplified encryption strategy. The model considers both local and global IoT environments and implements an authentication mechanism using challenge-response exchanges between communicating nodes. A digital signature is generated using parameters like random seeds, secret keys, prime values, and data packets. Simulation results show that the proposed system offers efficient security and data transmission performance in the presence of unknown adversaries, performing better than commonly used security solutions in vulnerable IoT environments.
Privacy-aware secured discrete framework in wireless sensor networkIJECEIAES
Rapid expansion of wireless sensor network-internet of things (WSN-IoT) in terms of application and technologies has led to wide research considering efficiency and security aspects. Considering the efficiency approach such as data aggregation along with consensus mechanism has been one of the efficient and secure approaches, however, privacy has been one of major concern and it remains an open issue due to low classification and high misclassification rate. This research work presents the privacy and reliable aware discrete (PRD-aggregation) framework to protect and secure the privacy of the node. It works by initializing the particular variable for each node and defining the threshold; further nodes update their state through the functions, and later consensus is developed among the sensor nodes, which further updates. The novelty of PRD is discretized transmission for efficiency and security. PRD-aggregation offers reliability through efficient termination criteria and avoidance of transmission failure. PRD-aggregation framework is evaluated considering the number of deceptive nodes for securing the node in the network. Furthermore, comparative analysis proves the marginal improvisation in terms of discussed parameter against the existing protocol.
AN EFFICIENT SECURE CRYPTOGRAPHY SCHEME FOR NEW ML-BASED RPL ROUTING PROTOCOL...IJNSA Journal
Internet of Things (IoT) offers reliable and seamless communication for the heterogeneous dynamic lowpower and lossy network (LLNs). To perform effective routing in IoT communication, LLN Routing Protocol (RPL) is developed for the tiny nodes to establish connection by using deflaut objective functions: OF0, MRHOF, for which resources are constraints like battery power, computation capacity, memory communication link impacts on varying traffic scenarios in terms of QoS metrics like packet delivery ratio, delay, secure communication channel. At present, conventional Internet of Things (IoT) are having secure communication channels issue for transmission of data between nodes. To withstand those issues, it is necessary to balance resource constraints of nodes in the network. In this paper, we developed a security algorithm for IoT networks with RPL routing. Initially, the constructed network in corporates optimizationbased deep learning (reinforcement learning) for route establishment in IoT. Upon the establishment of the route, the ClonQlearn based security algorithm is implemented for improving security which is based onaECC scheme for encryption and decryption of data. The proposed security technique incorporates reinforcement learning-based ClonQlearnintegrated with ECC (ClonQlearn+ECC) for random key generation. The proposed ClonQlearn+ECCexhibits secure data transmission with improved network performance when compared with the earlier works in simulation. The performance of network expressed that the proposed ClonQlearn+ECC increased the PDR of approximately 8% - 10%, throughput of 7% - 13%, end-to-end delay of 5% - 10% and power consumption variation of 3% - 7%.
Survey on Optimization of IoT Routing Based On Machine Learning TechniquesIRJET Journal
This document discusses several studies on using machine learning techniques to optimize routing in Internet of Things (IoT) networks. It first provides background on IoT and challenges with routing in IoT networks due to factors like device mobility and limited resources. It then summarizes several papers that propose different machine learning approaches for IoT routing, including using reinforcement learning to balance node loads and extend network lifetime, integrating deep reinforcement learning into existing routing protocols to improve performance, and using Q-learning at each node to learn optimal parent selection policies based on network conditions. Finally, it discusses a study that developed an energy-efficient routing algorithm for wireless sensor networks based on dynamic programming to maximize network lifetime.
A data quarantine model to secure data in edge computingIJECEIAES
Edge computing provides an agile data processing platform for latencysensitive and communication-intensive applications through a decentralized cloud and geographically distributed edge nodes. Gaining centralized control over the edge nodes can be challenging due to security issues and threats. Among several security issues, data integrity attacks can lead to inconsistent data and intrude edge data analytics. Further intensification of the attack makes it challenging to mitigate and identify the root cause. Therefore, this paper proposes a new concept of data quarantine model to mitigate data integrity attacks by quarantining intruders. The efficient security solutions in cloud, ad-hoc networks, and computer systems using quarantine have motivated adopting it in edge computing. The data acquisition edge nodes identify the intruders and quarantine all the suspected devices through dimensionality reduction. During quarantine, the proposed concept builds the reputation scores to determine the falsely identified legitimate devices and sanitize their affected data to regain data integrity. As a preliminary investigation, this work identifies an appropriate machine learning method, linear discriminant analysis (LDA), for dimensionality reduction. The LDA results in 72.83% quarantine accuracy and 0.9 seconds training time, which is efficient than other state-of-the-art methods. In future, this would be implemented and validated with ground truth data.
An efficient approach for secured communication in wireless sensor networks IJECEIAES
Wireless sensor network (WSN) have limited bandwidth, low computational functions, energy constraints. Inspite of these constraints, WSN is useful where communication happens without infrastructure support. The main concern of WSN is the security as the sensor nodes may be attacked and information may be hacked. Security of WSN should have the capability to ensure that the message received was sent by the particular sent node and not modified during transmission. WSN applications require lightweight and strong authentication mechanisms for obtaining data from unprivileged users. In wireless sensor networks, authentication is the effective method to stop unauthorized and undisrupted communication service. In order to strengthen the authenticated communication, several researchers have developed mechanisms. Some of the techniques work with identifying the attacked node or detecting injected bogus message in the network. Encryption and decryption are the popular methods of providing the security. These are based on either public-key or symmetric-key cryptosystems.Many of the existing solutions have limitations in communication and computational expertise. Also, the existing mechanisms lack in providing strength and scalability of the network. In order address these issues; a polynomial based method was introduced in recent days. Key distribution is a significant aspect in key management in WSNs. The simplest method of distribution of key is by hand which was used in the days of couriers. Now a day, most distribution of keys is done automatically. The automatic distribution of keys is essential and convenient in networks that require two parties to transmit their security keys in the same communication medium. In this work, a new type of key exchange mechanism is proposed. The proposed method for authentication among sensor nodes proves to be promising as per the simulation results. The nodes which are unknown to each other setup a private however arbitrary key for the symmetric key cryptosystem.
Multi-stage secure clusterhead selection using discrete rule-set against unkn...IJECEIAES
The document discusses a proposed multi-stage secure clusterhead selection technique for wireless sensor networks using a discrete rule-set. The technique aims to securely select clusterheads during the data aggregation process and learn the nature of communications to gain knowledge about adversary intensity. It constructs primary and secondary rule-sets to filter and select secure clusterheads based on energy, neighbors, vulnerability, vicinity and distance from adversaries. Simulation results using MEMSIC sensor nodes showed the proposed approach reduces energy consumption and improves data delivery compared to existing methods.
SECURITY AND PRIVACY AWARE PROGRAMMING MODEL FOR IOT APPLICATIONS IN CLOUD EN...ijccsa
This document summarizes a research paper on privacy-preserving techniques for IoT data in cloud environments. It introduces two differential privacy algorithms: 1) Generic differential privacy (GenDP) which provides generalized privacy protection for homogeneous and heterogeneous IoT metadata through data portioning. 2) Cluster-based differential privacy which groups similar data into clusters before defining classifiers to validate privacy. The paper evaluates these techniques and finds the cluster-based approach offers better security than customized interactive algorithms while maintaining data utility. Overall, the study presents new differential privacy methods for anonymizing IoT metadata stored in the cloud.
Trust correlation of mobile agent nodes with a regular node in a Adhoc networ...IJECEIAES
A mobile agent offers discrete advantage both in facilitating better transmission as well as controlling the traffic load in Mobile Adhoc Network (MANET). Hence, such forms of network offers maximized dependencies on mobile agents in terms of its trust worthiness. At present, there are various work being carried out towards resisting security breach in MANET; however approaches using mobile agent based mechanism is few to found. Therefore, the proposed system introduces a novel mathematical model where an extensive decision making system has been constructed for identifying the malicious intention of mobile agents in case they go rogues. By adopting multi-tier communication policy and fairness concept, the proposed system offers the capability to resist any form of malicious activity of mobile agent without even presence of any apriori information of adversary. The outcome shows proposed system outshines existing security scheme in MANET.
Secure Channel Communication between IOT Devices and ComputersIRJET Journal
The document proposes a model to establish secure communication channels between IoT devices and computers/servers. The model implements encryption algorithms like RSA to encrypt data transmitted between IoT devices and an unconstrained node (computer/server). This helps create secure channels for transmitting encrypted data while offloading intensive encryption tasks to more powerful unconstrained nodes. The model aims to address growing security and privacy concerns with the proliferation of IoT devices and applications.
Novel authentication framework for securing communication in internet-of-things IJECEIAES
Internet-of-Things (IoT) offers a big boon towards a massive network of connected devices and is considered to offer coverage to an exponential number of the smart appliance in the very near future. Owing to the nascent stage of evolution of IoT, it is shrouded by security loopholes because of various reasons. Review of existing research-based solution highlights the usage of conventional cryptographic-based solution over the traditional mechanism of data forwarding process between IoT nodes and gateway. The proposed system presents a novel solution to this problem by a model that is capable of performing a highly secured and cost-effective authentication process. The proposed system introduces Authentication Using Signature (AUS) as well as Security with Complexity Reduction (SCR) for the purpose to resist participation of any form of unknown threats. The outcome of the model shows better security strength with faster response time and energy saving of the IoT nodes.
Integrated Framework for Secure and Energy Efficient Communication System in ...IJECEIAES
Irrespective of different forms and strategies implementing for securing Wireless Sensor Network (WSN), there are very less strategies that offers cost effective security over heterogeneous network. Therefore, this paper presents an integrated set of different processes that emphasize over secure routing, intellectual and delay-compensated routing, and optimization principle with a sole intention of securing the communication to and from the sensor nodes during data aggregation. The processed system advocates the non-usage of complex cryptography and encourages the usage of probability their and analytical modelling in order to render more practical implementation. The simulated outcome of study shows that proposed system offers reduced delay, more throughputs, and reduced energy consumption in contrast to existing system.
A new algorithm to enhance security against cyber threats for internet of thi...IJECEIAES
One major problem is detecting the unsuitability of traffic caused by a distributed denial of services (DDoS) attack produced by third party nodes, such as smart phones and other handheld Wi-Fi devices. During the transmission between the devices, there are rising in the number of cyber attacks on systems by using negligible packets, which lead to suspension of the services between source and destination, and can find the vulnerabilities on the network. These vulnerable issues have led to a reduction in the reliability of networks and a reduction in consumer confidence. In this paper, we will introduce a new algorithm called rout attack with detection algorithm (RAWD) to reduce the affect of any attack by checking the packet injection, and to avoid number of cyber attacks being received by the destination and transferred through a determined path or alternative path based on the problem. The proposed algorithm will forward the real time traffic to the required destination from a new alternative backup path which is computed by it before the attacked occurred. The results have showed an improvement when the attack occurred and the alternative path has used to make sure the continuity of receiving the data to the main destination without any affection.
Security Issues and Challenges in Internet of Things – A ReviewIJERA Editor
The Internet of Things (IoT) alludes to the continually developing system of physical articles that component an
IP address for web availability, and the correspondence that happens between these items and other Web
empowered gadgets and frameworks. The security issues of the Internet of Things (IoT) are straight forwardly
identified with the wide utilization of its framework. IoT securities and enhancing the design and several
elements of this work showcases various security issues with respect to IoT and thinks of solutions for the issues
under the advancements included. Here we are going to do a study of all the security issues existing in the
Internet of Things (IoT) alongside an examination of the protection issues that an end-client might confront as
an outcome of the spread of IoT. Most of the overview is centred around the security emerging out of the data
trade innovations utilized as a part of Internet of Things. As a piece of IoTs, genuine concerns are raised over
access of individual data relating to gadget and individual protection. This review tells about the security and
protection issues of IoT.
Internet of things-blockchain lightweight cryptography to data security and ...IJECEIAES
The industrial internet of things (IoT) plays a major role in the growth of automation and increasing digital connectivity for machine-to-machine communication. The research community has extensively investigated the possibility of IoT and blockchain integration for the last couple of years. The major research is focused on the benefits of integrating blockchain with IoT. In this work, we first focus on the issue of integrating IoT nodes with blockchain networks, especially for non-real-time IoT nodes that do not have an in-built clock mechanism. As a result, they cannot establish communication with real-time blockchain networks. Another critical security issue is protecting data coming from IoT devices to blockchain networks. Blockchain is enough mature to protect the data in its ecosystem. However, information coming from outside of the world does not have any guarantee of data integrity and security. This paper first addresses the clock synchronization issue of IoT nodes with blockchain using a network time protocol and then proposes an IoT-blockchain light-weight cryptographic (IBLWC) approach to secure the entire IoT-blockchain ecosystem. This paper also presents the performance analysis of IBLWC as a suitable and cost-effective solution that incurs less processing overhead for IoTblockchain-based applications.
IRJET- An Intrusion Detection and Protection System by using Data Mining ...IRJET Journal
This document proposes an Internal Intrusion Detection and Protection System (IIDPS) to detect insider attacks by analyzing system calls (SCs) using data mining and forensic techniques. The IIDPS creates personal profiles for each user to track their computer usage behaviors over time. When a user logs in, the IIDPS compares their current behaviors to the patterns in their personal profile to determine if they are the legitimate account holder or an unauthorized insider attacker. The IIDPS aims to more accurately authenticate users and detect insider threats compared to existing systems that rely only on usernames and passwords.
Deep Learning and Big Data technologies for IoT SecurityIRJET Journal
The document discusses using deep learning and big data technologies to improve security for Internet of Things (IoT) devices and networks. Specifically, it proposes using deep learning models to analyze large amounts of data from IoT sensors to better detect and classify security threats. This can help identify attacks like botnets and distributed denial-of-service (DDoS) attacks. The document also outlines some common IoT security challenges and how approaches like Apache Hadoop, Spark, and Storm can process large volumes of IoT data to improve real-time monitoring and threat prevention.
Pervasive and ubiquitous computing has enabled people better integrate physical things into the digital world. The internet of things (IoT) has been considerably more widely used in business and everyday life in the last decade. Innovative healthcare information and communication technologies are a vast field of research and applications that need IoT benefits, including speed, security, and low cost. The proposed modified advanced encryption standard (AES)-cipher block chaining (CBC)-based blockchain technology offers a shared key to devices that need to communicate directly with or with entities outside the smart healthcare network to give users greater control over transactions. The experiments are carried out using a Raspberry Pi 3, whereas two different sensors are employed in this case. Blockchain technology encrypts data between doctor and patient with varied user numbers. The results from experiments revealed that the proposed modified AES-CBC based blockchain technology could provide the IoT application with security services (confidentiality, integrity, and access control) with efficient execution time.
A secure trust-based protocol for hierarchical routing in wireless sensor ne...IJECEIAES
Wireless sensor networks (WSNs) became the backbone of the internet of things (IoT). IoT applications are vital and demand specific quality of service (QoS) requirements. In addition, security has become a primary concern to provide secure communication between wireless nodes, with additional challenges related to the node’s computational resources. Particular, the design of secure and resource efficient routing protocol is a critical issue in the current deployment of WSNs. Therefore, this paper proposes a novel secure-trust aware routing protocol (ST2A) that provides secure and reliable routing. The proposed protocol establishes communication routes based on calculated trust value in joint with a novel cluster head selection algorithm in the hierarchical routing process. The proposed trust-aware routing algorithm improves the routing security in WSN and optimizes many performance metrics related to WSNs unique characteristics. The results of simulation validate the feasibility of the proposed algorithm for enhancing the network lifetime up to 18% and data delivery by 17% as compared with some state-of-the-art routing algorithms.
This document discusses challenges and techniques for securing Internet of Things (IoT) architecture. It begins with an introduction to IoT and outlines key challenges including privacy, security, scalability, and connectivity issues that arise from the large number of interconnected devices. The document then reviews literature on techniques for securing IoT, such as using network function virtualization (NFV) and information-centric networking (ICN). It describes several proposed secure IoT architectures in detail and compares different approaches. The document concludes by discussing future directions for securing IoT architecture.
IRJET- Revisiting Security Aspects of Internet of Things for Self-Managed...IRJET Journal
This document discusses security aspects of internet of things (IoT) devices and proposes solutions. It summarizes 3 existing approaches:
1) An IoT reference model that includes authorization, encryption, and authentication mechanisms at each layer independently.
2) A protocol for IoT security using elliptic curve cryptography to allow encryption and decryption of messages between devices and gateways.
3) A mechanism using elliptic curve cryptography to provide security for communication between IPv4 and IPv6 networks, translating addresses and incorporating encryption.
The document also motivates the need for lightweight cryptographic algorithms for resource-constrained IoT devices and surveys existing schemes to provide confidentiality, integrity, and availability while addressing vulnerabilities.
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODELgerogepatton
As digital technology becomes more deeply embedded in power systems, protecting the communication
networks of Smart Grids (SG) has emerged as a critical concern. Distributed Network Protocol 3 (DNP3)
represents a multi-tiered application layer protocol extensively utilized in Supervisory Control and Data
Acquisition (SCADA)-based smart grids to facilitate real-time data gathering and control functionalities.
Robust Intrusion Detection Systems (IDS) are necessary for early threat detection and mitigation because
of the interconnection of these networks, which makes them vulnerable to a variety of cyberattacks. To
solve this issue, this paper develops a hybrid Deep Learning (DL) model specifically designed for intrusion
detection in smart grids. The proposed approach is a combination of the Convolutional Neural Network
(CNN) and the Long-Short-Term Memory algorithms (LSTM). We employed a recent intrusion detection
dataset (DNP3), which focuses on unauthorized commands and Denial of Service (DoS) cyberattacks, to
train and test our model. The results of our experiments show that our CNN-LSTM method is much better
at finding smart grid intrusions than other deep learning algorithms used for classification. In addition,
our proposed approach improves accuracy, precision, recall, and F1 score, achieving a high detection
accuracy rate of 99.50%.
International Refereed Journal of Engineering and Science (IRJES)irjes
The core of the vision IRJES is to disseminate new knowledge and technology for the benefit of all, ranging from academic research and professional communities to industry professionals in a range of topics in computer science and engineering. It also provides a place for high-caliber researchers, practitioners and PhD students to present ongoing research and development in these areas.
The document provides a survey of trust management techniques for the Internet of Things (IoT). It summarizes four key trust management techniques:
1) E-LITHE enhances DTLS security for constrained IoT devices by adding a trusted third party to share secret keys and reduce denial-of-service attacks.
2) GTRS is a graph-based recommender system that calculates trust between IoT devices based on ratings and social relationships to select trusted service providers.
3) TWGA is a trustworthy gateway architecture that establishes trusted paths between domains using device identifiers and public/private keys to authenticate and forward data packets securely.
4) TBBS monitors the behavior and trust of vehicles in an Io
HISTOGRAM OF NEIGHBORHOOD TRIPARTITE AUTHENTICATION WITH FINGERPRINT-BASED BI...IJCNCJournal
Internet of Things (IoT) and services is an interesting topic with a wide range of potential applications like smart home systems, health care, telemedicine, and intelligent transportation. Traditionally, key agreement schemes have been evaluated to access IoT services which are highly susceptible to security. Recently, Biometric-based authentication is also used to access IoT services and devices. They are involving a larger amount of memory with increased running time and found to be computationally infeasible. To provide robust authentication for IoT services, Histogram of Neighborhood Tripartite Authentication with Fingerprint Biometrics (HNTA-FB) for IoT services is proposed in this paper. This proposed HNTA-FB method uses binary patterns and a histogram of features to extract the region of interest. To reduce the memory requirements while providing access to IoT services, Histogram of Neighborhood Binary Pattern Pre-processing (HNBPP) model is proposed. The discriminative power of Neighbourhood Binary Pattern Registration (NBPR) is integrated with the normalized sparse representation based on the histogram. Additionally, this work presents a new Tripartite User Authentication model for fingerprint biometric template matching process. When compared with different state-of-the-art methods, the proposed method depicts significantly improved performance in terms of matching accuracy, computational overhead and execution speed and is highly effective in delivering smart home services.
PRIVACY-PRESERVING MACHINE AUTHENTICATED KEY AGREEMENT FOR INTERNET OF THINGSIJCNCJournal
This document proposes a new privacy-preserving machine authenticated key agreement (AKA) protocol for the Internet of Things (IoT) called IoTMAKA. The protocol aims to eliminate human factors in IoT authentication by using machine biometrics like machine fingerprints. It also prioritizes privacy over security to protect the anonymity and untraceability of communicating entities. IoTMAKA is designed to reduce computational and communication overheads to improve efficiency compared to previous related works. The protocol involves three entities - an IoT device, a central server, and a service server. The central server authenticates the IoT device and service server and facilitates secure communication and key agreement between them.
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...IJECEIAES
Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the model’s competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
imaging, emphasizing addressing false positives and resource efficiency.
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
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Secure Channel Communication between IOT Devices and ComputersIRJET Journal
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Internet-of-Things (IoT) offers a big boon towards a massive network of connected devices and is considered to offer coverage to an exponential number of the smart appliance in the very near future. Owing to the nascent stage of evolution of IoT, it is shrouded by security loopholes because of various reasons. Review of existing research-based solution highlights the usage of conventional cryptographic-based solution over the traditional mechanism of data forwarding process between IoT nodes and gateway. The proposed system presents a novel solution to this problem by a model that is capable of performing a highly secured and cost-effective authentication process. The proposed system introduces Authentication Using Signature (AUS) as well as Security with Complexity Reduction (SCR) for the purpose to resist participation of any form of unknown threats. The outcome of the model shows better security strength with faster response time and energy saving of the IoT nodes.
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Security Issues and Challenges in Internet of Things – A ReviewIJERA Editor
The Internet of Things (IoT) alludes to the continually developing system of physical articles that component an
IP address for web availability, and the correspondence that happens between these items and other Web
empowered gadgets and frameworks. The security issues of the Internet of Things (IoT) are straight forwardly
identified with the wide utilization of its framework. IoT securities and enhancing the design and several
elements of this work showcases various security issues with respect to IoT and thinks of solutions for the issues
under the advancements included. Here we are going to do a study of all the security issues existing in the
Internet of Things (IoT) alongside an examination of the protection issues that an end-client might confront as
an outcome of the spread of IoT. Most of the overview is centred around the security emerging out of the data
trade innovations utilized as a part of Internet of Things. As a piece of IoTs, genuine concerns are raised over
access of individual data relating to gadget and individual protection. This review tells about the security and
protection issues of IoT.
Internet of things-blockchain lightweight cryptography to data security and ...IJECEIAES
The industrial internet of things (IoT) plays a major role in the growth of automation and increasing digital connectivity for machine-to-machine communication. The research community has extensively investigated the possibility of IoT and blockchain integration for the last couple of years. The major research is focused on the benefits of integrating blockchain with IoT. In this work, we first focus on the issue of integrating IoT nodes with blockchain networks, especially for non-real-time IoT nodes that do not have an in-built clock mechanism. As a result, they cannot establish communication with real-time blockchain networks. Another critical security issue is protecting data coming from IoT devices to blockchain networks. Blockchain is enough mature to protect the data in its ecosystem. However, information coming from outside of the world does not have any guarantee of data integrity and security. This paper first addresses the clock synchronization issue of IoT nodes with blockchain using a network time protocol and then proposes an IoT-blockchain light-weight cryptographic (IBLWC) approach to secure the entire IoT-blockchain ecosystem. This paper also presents the performance analysis of IBLWC as a suitable and cost-effective solution that incurs less processing overhead for IoTblockchain-based applications.
IRJET- An Intrusion Detection and Protection System by using Data Mining ...IRJET Journal
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A secure trust-based protocol for hierarchical routing in wireless sensor ne...IJECEIAES
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This document discusses challenges and techniques for securing Internet of Things (IoT) architecture. It begins with an introduction to IoT and outlines key challenges including privacy, security, scalability, and connectivity issues that arise from the large number of interconnected devices. The document then reviews literature on techniques for securing IoT, such as using network function virtualization (NFV) and information-centric networking (ICN). It describes several proposed secure IoT architectures in detail and compares different approaches. The document concludes by discussing future directions for securing IoT architecture.
IRJET- Revisiting Security Aspects of Internet of Things for Self-Managed...IRJET Journal
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2) A protocol for IoT security using elliptic curve cryptography to allow encryption and decryption of messages between devices and gateways.
3) A mechanism using elliptic curve cryptography to provide security for communication between IPv4 and IPv6 networks, translating addresses and incorporating encryption.
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As digital technology becomes more deeply embedded in power systems, protecting the communication
networks of Smart Grids (SG) has emerged as a critical concern. Distributed Network Protocol 3 (DNP3)
represents a multi-tiered application layer protocol extensively utilized in Supervisory Control and Data
Acquisition (SCADA)-based smart grids to facilitate real-time data gathering and control functionalities.
Robust Intrusion Detection Systems (IDS) are necessary for early threat detection and mitigation because
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solve this issue, this paper develops a hybrid Deep Learning (DL) model specifically designed for intrusion
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(CNN) and the Long-Short-Term Memory algorithms (LSTM). We employed a recent intrusion detection
dataset (DNP3), which focuses on unauthorized commands and Denial of Service (DoS) cyberattacks, to
train and test our model. The results of our experiments show that our CNN-LSTM method is much better
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our proposed approach improves accuracy, precision, recall, and F1 score, achieving a high detection
accuracy rate of 99.50%.
International Refereed Journal of Engineering and Science (IRJES)irjes
The core of the vision IRJES is to disseminate new knowledge and technology for the benefit of all, ranging from academic research and professional communities to industry professionals in a range of topics in computer science and engineering. It also provides a place for high-caliber researchers, practitioners and PhD students to present ongoing research and development in these areas.
The document provides a survey of trust management techniques for the Internet of Things (IoT). It summarizes four key trust management techniques:
1) E-LITHE enhances DTLS security for constrained IoT devices by adding a trusted third party to share secret keys and reduce denial-of-service attacks.
2) GTRS is a graph-based recommender system that calculates trust between IoT devices based on ratings and social relationships to select trusted service providers.
3) TWGA is a trustworthy gateway architecture that establishes trusted paths between domains using device identifiers and public/private keys to authenticate and forward data packets securely.
4) TBBS monitors the behavior and trust of vehicles in an Io
HISTOGRAM OF NEIGHBORHOOD TRIPARTITE AUTHENTICATION WITH FINGERPRINT-BASED BI...IJCNCJournal
Internet of Things (IoT) and services is an interesting topic with a wide range of potential applications like smart home systems, health care, telemedicine, and intelligent transportation. Traditionally, key agreement schemes have been evaluated to access IoT services which are highly susceptible to security. Recently, Biometric-based authentication is also used to access IoT services and devices. They are involving a larger amount of memory with increased running time and found to be computationally infeasible. To provide robust authentication for IoT services, Histogram of Neighborhood Tripartite Authentication with Fingerprint Biometrics (HNTA-FB) for IoT services is proposed in this paper. This proposed HNTA-FB method uses binary patterns and a histogram of features to extract the region of interest. To reduce the memory requirements while providing access to IoT services, Histogram of Neighborhood Binary Pattern Pre-processing (HNBPP) model is proposed. The discriminative power of Neighbourhood Binary Pattern Registration (NBPR) is integrated with the normalized sparse representation based on the histogram. Additionally, this work presents a new Tripartite User Authentication model for fingerprint biometric template matching process. When compared with different state-of-the-art methods, the proposed method depicts significantly improved performance in terms of matching accuracy, computational overhead and execution speed and is highly effective in delivering smart home services.
PRIVACY-PRESERVING MACHINE AUTHENTICATED KEY AGREEMENT FOR INTERNET OF THINGSIJCNCJournal
This document proposes a new privacy-preserving machine authenticated key agreement (AKA) protocol for the Internet of Things (IoT) called IoTMAKA. The protocol aims to eliminate human factors in IoT authentication by using machine biometrics like machine fingerprints. It also prioritizes privacy over security to protect the anonymity and untraceability of communicating entities. IoTMAKA is designed to reduce computational and communication overheads to improve efficiency compared to previous related works. The protocol involves three entities - an IoT device, a central server, and a service server. The central server authenticates the IoT device and service server and facilitates secure communication and key agreement between them.
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Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...IJECEIAES
Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
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compared to traditional linear models. This study underscores the
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insights into the intricate relationships between state-of-charge, voltage, and
current under dynamic conditions.
Smart grid deployment: from a bibliometric analysis to a surveyIJECEIAES
Smart grids are one of the last decades' innovations in electrical energy.
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evolution is essential to propose guidelines for facing new and future smart
grid challenges. In addition, knowing the main technologies involved in the
deployment of smart grids (SGs) is important to highlight possible
shortcomings that can be mitigated by developing new tools. This paper
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objectives. First, a bibliometric analysis is presented to give an overview of
the current research level about smart grid deployment. Second, a survey of
the main technological approaches used for smart grid implementation and
their contributions are highlighted. To that effect, we searched the Web of
Science (WoS), and the Scopus databases. We obtained 5,663 documents
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research.
Use of analytical hierarchy process for selecting and prioritizing islanding ...IJECEIAES
One of the problems that are associated to power systems is islanding
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weight of passive methods (24.7%), active methods (7.8%), hybrid methods
(5.6%), remote methods (14.5%), signal processing-based methods (26.6%),
and computational intelligent-based methods (20.8%) based on the
comparison of all criteria together. Thus, it can be seen from the total weight
that hybrid approaches are the least suitable to be chosen, while signal
processing-based methods are the most appropriate islanding detection
method to be selected and implemented in power system with respect to the
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the errors, and significantly reduces chattering. First, the synchronous tracking
errors and synchronous sliding surfaces are presented. Second, the synchronous
tracking error dynamics are determined. Third, a robust adaptive control law is
designed,the unknown components of the model are estimated online by the neural network, and the parameters of the switching elements are selected by fuzzy
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A trust based secure access control using authentication mechanism for interoperability in internet of things
1. International Journal of Electrical and Computer Engineering (IJECE)
Vol. 14, No. 2, April 2024, pp. 2262~2273
ISSN: 2088-8708, DOI: 10.11591/ijece.v14i2.pp2262-2273 2262
Journal homepage: http://ijece.iaescore.com
A trust based secure access control using authentication
mechanism for interoperability in internet of things
Shashikala Narayanappa1
, Tulavanur Narayanareddy Anitha2
, Priti Mishra3
, Renuka Patil Herakal4
,
Jayasudha Kolur5
1
Department of Computer Science and Engineering, REVA University and Research Scholar,
Affiliated to Visvesvaraya Technological University, Belagavi, India
2
Department of Computer Science and Engineering, Sir M. Visvesvaraya Institute of Technology, Bengaluru, India
3
Department of Information Science and Engineering, Atria Institute of Technology, Bengaluru, India
4
Department of Computer Science and Engineering, GITAM (deemed to be) University, Bengaluru, India
5
Department of Artificial Intelligence and Machine Learning, Sri Krishna Institute of Technology, Bengaluru, India
Article Info ABSTRACT
Article history:
Received Jul 8, 2023
Revised Sep 30, 2023
Accepted Oct 20, 2023
The internet of things (IoT) is a revolutionary innovation in many aspects of
our society including interactions, financial activity, and global security such
as the military and battlefield internet. Due to the limited energy and
processing capacity of network devices, security, energy consumption,
compatibility, and device heterogeneity are the long-term IoT problems. As
a result, energy and security are critical for data transmission across edge
and IoT networks. Existing IoT interoperability techniques need more
computation time, have unreliable authentication mechanisms that break
easily, lose data easily, and have low confidentiality. In this paper, a key
agreement protocol-based authentication mechanism for IoT devices is
offered as a solution to this issue. This system makes use of information
exchange, which must be secured to prevent access by unauthorized users.
Using a compact contiki/cooja simulator, the performance and design of the
suggested framework are validated. The simulation findings are evaluated
based on detection of malicious nodes after 60 minutes of simulation. The
suggested trust method, which is based on privacy access control, reduced
packet loss ratio to 0.32%, consumed 0.39% power, and had the greatest
average residual energy of 0.99 mJoules at 10 nodes.
Keywords:
Contiki/cooja simulator
Internet of things
Interoperability
Routing protocol for low-power
and lossy networks
Trust based mechanism
Wireless sensor networks
This is an open access article under the CC BY-SA license.
Corresponding Author:
Shashikala Narayanappa
Department of Computer Science and Engineering, REVA University and Research Scholar, Affiliated to
Visvesvaraya Technological University
Belagavi, Karnataka, India
Email: Shashikalan2006@gmail.com
1. INTRODUCTION
The interrelated physical devices in a network interact with one another to facilitate smart decision-
making by keeping track of analyzing their environment. Organizations focus drastically on the internet for
regular communication within the organization as well as long-distance company conferences. Networks or
devices in a smart city, industrial automation, and households are now linked to the internet, allowing for
faster and more efficient communication [1], [2]. The internet of things (IoT) is used as an information
network in most real-world applications. It links multiple devices and system components via enhanced
information and communication technology (ICT) and improved embedded devices such as digitalized
sensors, meters, and controllers [3]. Wireless sensor networks (WSNs) have greatly enhanced the technology
utilization of IoT, which primarily includes gathering and sending information over wireless channels.
2. Int J Elec & Comp Eng ISSN: 2088-8708
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IoT based protocols for authentication are suggested to offer user anonymity against malicious users and
inactive adversaries to satisfy the security characteristics of the session key, forward secrecy, mutual
authentication, and IoT security [4], [5].
The challenge of security in information technology has existed for a long time and has been
focused on multiple levels, such as networking, syntactic, and semantic levels, as well as numerous domains
like industrial and healthcare domains [6]–[8]. In the real world, safe and secure connections are primary
challenges due to the heterogeneity of IoT tools, and the shortage of resources, while some of the resources
connected to the internet protocol (IP) hosts are powerful. Furthermore, IoT-connected devices must be
secure with authentications like end-to-end (E2E) connections [9]–[11]. Like other networks, IoT security is
dependent on confidentiality and trust. As a result, attack detection systems are one of the primary defense
methods against IoT attacks. The frequent occurrence of IoT attacks results in financial loss or worse.
Attestation is a low-cost method of identifying malicious devices. However, providing authentication
between device-to-device approaches costs more in terms of authentication time, communication overhead,
as well as scalability issues. Therefore, new attestation technologies which are dependable and scalable need
to be protected for network operations involving IoT devices [12]–[15]. To normalize and stabilize the
security needs of IoT's physical, network, and application layers, energy consumption must be reduced [16].
Cloud computing technology provides the base foundation and storage for data processes in IoT, and
methodologies based on cloud cryptography are presented as a standout compared to other approaches to
ensure data security in many IoT applications [17]. Most conventional security methods are not up to snuff to
protect the industrial strategies of most firms and business sectors. The root exploit, botnets, spyware, worm,
and Trojan are some of the critical IoT security issues to be dealt with [18]. Different IoT devices has
different security requirements such as security built into the device, security of information
communications, information storage inside frameworks, and its application [19], [20]. Poor security
measures lead to the cause of various attacks in the network which prevents packets from being received at
the border route. The packet distribution in the network is mostly influenced by the black hole attacks and
sinkhole attacks [21]. The black hole attacks happen when an attacker node acts as a single node. The
sinkhole attacks occur when the intruder attempts to attract possible paths allowing him to control the
circulation of data in the network. Due to these attacks, the energy efficiency of the nodes will be reduced
which results in the less data packets delivery [22]. The objective of these attacks is to tamper the
neighbourhood which affects the routing operations, getting more resources, and exploitation. Hence to
overcome these attacks, a secure routing protocols must be developed to avoid attacks and eliminate
malicious nodes from the network. The improvement of quality of service (QoS) parameters such as latency,
delivery of packets, resource utilization and so on, can also enhance the networks routing [23], [24].
Some of the existing researches based on IoT interoperability are described as: Anuradha et al. [25]
developed a system to predict cancer using the internet of things to test whether blood results were normal or
abnormal by improving security enhancement and authentication in the cloud area. The processing and
enhancement of healthcare computations through encryption and decryption with the advanced encryption
standard (AES) algorithm was the primary intention of this work. Encryption was performed on the reports of
cancer patients and saved in the cloud database for quick analysis through the Internet by healthcare nurses or
doctors to manage the patient data confidential. This proposed approach has achieved the highest efficiency,
system performance and throughput compared to the existing encryption systems. However, this approach
was not suitable to detect all types of cancer-related to blood, skin, breast, and lungs. Abbasi et al. [26]
proposed a multi-layer framework to address the interoperability issues in heterogeneous IoTs and design an
interoperability framework with trust-based parameters. Various interaction services with different time
intervals have been tested with this approach along with the analysis of the decay rate. The overall
performance in terms of reliability and availability is high with this service-oriented framework. However,
this framework did not help operate communications between dependent services and applications. For
further investigation, artificial intelligence (AI) techniques can improve the overall procedure of trust
measurements.
Gali and Nidumolu [27] presented a chaotic bumble bees mating optimization (CBBMO) for secure
data transmission with trust sensing model (CBBMOR-TSM) to design trust model with secure routing. The
bumble bees mating optimization (BBMO) is stimulated by the mating nature of a swarm of bumble bees. To
improve the convergence rate of the BBMO technique, the CBBMO model is defined by the integration of
chaotic concept into the classical BBMO technique. This method has achieved better results in detecting
malicious nodes and also in developing secure routing path with trust parameters. However, due to limited
IoT resources in this method, there is drawback in performing data aggregation. Dhurandher et al. [28]
presented a cooperative and feedback-based trustable energy-efficient routing protocol (CFTEERP) to
overcome the issues in generic data communications due to complex security algorithms. This protocol
calculates local trust value (LTV) and global trust value (GTV) of each node using node attributes and
K-means-based feedback evaluation procedures. With the proposed protocol, the method has achieved better
3. ISSN: 2088-8708
Int J Elec & Comp Eng, Vol. 14, No. 2, April 2024: 2262-2273
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results in building energy and trust routing path but efficient trust validations are not carried out which is a
major drawback. Zhang et al. [29] presented an energy-efficient multilevel secure routing (EEMSR) protocol
to consider clustering for reasonable solution of conserving energy. A cluster-based multihop routing
protocol was utilized to reduce the high communication overhead due to the scalability of IoT networks. This
approach has achieved better results in achieving an energy-efficient and secure routing but there is a high
latency requirement in IoT applications, which is a major drawback.
Djedjig et al. [30] metric-based routing protocol for low-power and lossy networks (RPL)
trustworthiness scheme (MRTS) to address the issues of security concerns in RPL by evaluating trust
parameters and developing a secure routing network. According to simulations, the proposed approach was
effective by means of throughput, energy usage, rank changes of nodes, and packet delivery ratio.
Additionally, a mathematical modeling analysis demonstrates that trust based routing has the isotonicity and
monotonicity qualities necessary for routing and that MRTS satisfies the consistency, optimality, and loop-
freeness requirements. It is claimed that MRTS can be used as a technique for the repeated dilemma of
prisoner’s and that this will show its cooperative enforcement characteristic. MRTS needs to meet further
requirements, like movement, and have its services tested towards different trust thresholds. The RPL
protocol has been protected from insider attacks, according to Hassan et al. [31], who provided a variety of
trust-based techniques. As a result, a hierarchical trust-based technique called CTrust-RPL was recommended
for evaluating node trust based on their forwarding actions. To conserve computing, storage, and energy
resources at the node level, this study sends difficult trust-related computations to the controller, a higher
layer. To address the expanding demands of distributed IoT deployments and counter additional potential
assaults, the C-Trust model must create a distributed and more scalable trust-based approach.
Boualam et al. [32] suggested an efficient and secure RPL with an improved Diffie-Hellman
algorithm to provide authentication and integrity of RPL data. The developed approach employed an
objective function to decide the optimal paths precisely. The developed optimal path has achieved better
results in transferring packets with required security measures. The security properties of the protocols were
specified by using the automatic validation of internet security protocols and applications. The high security
level was provided for the secret key exchange among IoT nodes. However, this approach consumed more
energy and most of the trust parameters were neglected, which is a limitation of this work. Oukessou et al.
[33] have introduced an improved uplink throughput and energy efficiency long-range wide area network
(LoRAWAN) using 2 hop low energy adaptive clustering hierarchical routing protocol (LEACH). The long
range (LoRA) utilize chirp spread spectrum (CSS) technique that utilize wideband linear frequency of chirp
pulses to modulate the information of the signal. Moreover, a spreading factor was used to parameterize the
values which ranges from 7 to 12. The suggested approach minimizes the energy consumption of nodes by
uniformly distributing energy to each node. But, the gateway present in the LoRAWAN cannot respond for
both the slots. Hassani et al. [34] have introduced multi-constraints-based objective function with adaptive
stability (MCAS-OF) to indicate the radio strength, node energy consumption with parent selection approach.
The suggested approach considers the stability of the network by utilizing an adaptive threshold by
considering multi-constraint metrics. The suggested approach balances the workload among the nodes with
minimal latency during packet transmission. However, MCAS-OF does not achieve better result when it was
tested on real sky mote platform.
The major contributions to this work are listed: i) A key agreement-based mechanism with
authentication provides IoT devices by assessing the behavior of node trust in the RPL networks. This
method also achieved less computational storage and bandwidth, efficient energy, and the highest throughput
at the node level; ii) Secure data access is achieved between nodes in the network using secure and trust
based RPL networks and the trust parameters of the network are validated using the contiki/cooja simulator;
iii) To achieve secure information exchange and low computational complexity, a secure access control with
the key agreement is introduced into the network. Due to this, only authorized users can access the
information. The present manuscript is organized as follows: section 2 describes the proposed methodology
of this work. Section 3 illustrates results along with a comparative analysis of performance metrics. Section 4
provides a conclusion of the work.
2. METHOD
The main aim of this work is to design an interoperability framework for privacy and security
enhancement through services provided by IoT. The proposed framework is divided into the things layer,
registration layer, and service handling layer as shown in Figure 1. Each layer in the framework is linked
with the next layer. For initial trust calculations, a dynamic parameter selection and weight assignment are
used. The proposed framework's design includes a focus on trust measurements like true value and trust
degree. Following the estimation of the aggregated trust value, the controller will keep updating the
4. Int J Elec & Comp Eng ISSN: 2088-8708
A trust based secure access control using authentication mechanism for … (Shashikala Narayanappa)
2265
interaction table and the trustworthiness of IoT, and finally, the trust degree will be defined. Following that,
for each interaction, the value of trust is computed and shared within the interacted services by utilizing the
trust factor. Nonetheless, there are various important and dependent conditions in which interactions between
two or more IoT must be verified.
Figure 1. Flow chart of the proposed method
2.1. IoT devices
IoT service usage optimization necessitates the creation of new services from existing ones, which
can be accomplished by analyzing the combined relationships, context, and availability of services. Figure 1
represents the scenario of available physical devices in several application domains, where the service
domain refers to the geographic area with a different type of heterogeneous and homogeneous services. This
location could be a house, a park, a street, a building, a hospital, a bank, or anything else. The things layer
works as pass-through layer that takes information or request of service from various sources and routes them
to the layers below it for processing and completion. The most crucial gadgets connected to this layer include
sensors, smart gadgets, wearables, security cameras, and smart cars. The data request and service requests for
the next layer are carried out by this layer.
2.2. Registration phase
This layer utilizes features like device id, computing power, and memory to register devices and
their respective services. For the devices, all of this information is stored in the registration layer. It registers
the services, keeps their IDs in storage, and preserves all other pertinent data. IoT interactions should
therefore be categorized and managed following the registration layer namely service classification, privacy
and access control, trust management, and blockchain.
2.2.1. Login phase
This module focuses on another major concern among IoT devices i.e., privacy. Since IoT is
integrated with human daily life, appropriate preservations of privacy must be implemented for end users.
The emphasis of this module is on implementing various rules for restricting access to services and sharing of
resources. Overall, acquisition issues are resolved. Data security, secure data exchange, distributed access of
data and its access permissions are the main responsibilities. The definition of user and application privacy
policies is another goal of this module. Additionally, it will safeguard users' privacy.
2.3. Authentication phase
The context-aware secure services to requesters in the IoT context and a key component of trust
measurement, and it has evolved into a driving force to meet future IoT privacy and security requirements.
The main objective of this module is to offer dependable access to the IoT services that are currently offered.
The proposed authentication mechanism enables users for secure communication through IoT devices by
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Int J Elec & Comp Eng, Vol. 14, No. 2, April 2024: 2262-2273
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initializing trust parameters in the network. This section discusses the proposed trust based RPL mechanism,
which supports analyzing IoT node trust behavior and correcting behaviors of network management by
finding and blocking malicious nodes if suspicious signs are detected. The proposed method establishes the
trust among uncertainty between the nodes based upon the computation of the trustworthiness of nodes and
their uncertainty in trust value. It is more specifically the relationship between the quality of service provided
by two or more IoTs that exchange services. As a result, an IoT's activity is both a measure and a function of
trust. By the involvement of a belief theory among the key elements of the node the trust model computes the
uncertainty. The proposed model can work efficiently with the binary logic, where the node’s energy does
not strain in IoT devices. And by utilizing the calculations which are complex over the control layer the
adaptive trust parameters, can be determined by terms of packet loss ratio (PLR) and forwarding delay (FD)
parameters as input and detects the malicious nodes and remove them from the network by initiating certain
parameters as per trust calculation on each node of the network. The PLR and FD are the QoS parameters
used for trust calculation as shown in (1) and (2):
− Packet loss rate (𝑃𝐿𝑅): it is a ratio of packets dropped (𝑃𝑑) by the receiver nodes to the total packets (𝑃𝑡)
from the sender node, which is calculated using (1):
𝑃𝐿𝑅 =
𝑃𝑑
𝑃𝑡
(1)
− Forwarding delay (𝐹𝐷): the 𝐹𝐷 is the time interval between receiving a packet from the sender and then
forwarding it to the next node as shown in (2):
𝐹𝐷 = 𝑃𝑅 − 𝑃𝐹 (2)
where, 𝑃𝑅 is the packet received time, and 𝑃𝐹 is packet forwarding time.
The nodes are classified as trusted or untrusted by providing 0.5 threshold value, where trusted
nodes used for secure routing and communication. The node trust is updated using a time-based update
technique, which can detect rogue nodes in real time while simultaneously addressing high computational
challenges and low memory resources. Malicious nodes are removed from the network, and sensor nodes are
placed in the test region. The node trust is measured in terms of the success rate of the node as shown in (3)
and (4).
𝑇𝑆𝑅 =
𝑃𝐹
𝑃𝑅
⁄ (3)
𝑃𝐹 = 𝑃𝑅 − 𝑃𝐷 (4)
where, 𝑇𝑆𝑅 is the total success rate of the node, SR is the ratio of number of packets forwarded (𝑃𝐹), 𝑃𝑅 is the
number of packets received, and 𝑃𝐷 is number of packets dropped.
2.4. Key agreement phase
After completing the procedure of registration and trust calculation, an IoT intends to request and
access a huge range of services accessible on neighboring IoT. This layer serves as the basis for the service
management process. This layer stores all data that is relevant to the availability of services in the region.
Thus, service handling is inextricably linked with context management to dynamically embrace new
availability matrices in response to variations in sharing context-based updates accordingly. The logic used
to measure the terms b, u and d is based on the linear relationship between time and the parameters of
trust. The calculation is performed for each node, and the trust rating threshold is established. It is
determined to be a legitimate node of the network and can be included in routing after the rating of
propagation of trust is completed and it has the value of b always to be greater than a threshold; otherwise,
it will be removed. The proposed algorithm's complexity is reduced by the message overhead, and it is
O(n) in algorithmic form.
3. RESULTS
The effectiveness of the proposed trust based framework is evaluated using simulations. In this
paper, a contiki/cooja simulator is used for validation. Contiki can be used for high-performance and secure
communication between low-powered radio frequency identification (RFID) chips in wireless networks. The
proposed model uses attack detection, attack detection time, packet loss ratio, power consumption, and
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residual energy parameters to validate our mechanism. The following simulation setup has been used for the
evaluation of the proposed model topology as in Table 1.
Table 1. Simulation results of contiki/cooja simulator
Parameter Value
Area 70×70 m
No. of nodes 30
Tx ratio %
Rx ratio 30% to 100%
Malicious nodes 28, 29 and 30
Transmission range 50 m
Simulation time 60 minutes
Contiki/cooja simulator is used for the evaluation of the proposed network model, which is an open
source and light weight operating system. A total of 30 nodes are considered for evaluating the nodes trust
and to detect malicious nodes within the simulation time of 60 minutes. Results show that the proposed
mechanism detected three nodes 28, 29, and 30 as a malicious nodes out of 30 nodes. The results are
measured in terms of the packet loss ratio, attack detection and its time, power consumption, and residual
energy.
3.1. Quantitative evaluation
In this section, we compared the existing metric based RPL trustworthiness scheme (MRTS) [26]
and C Trust-RPL [27] with the proposed privacy access control-based trust mechanism. These methods are
compared in terms of performance metrics such as attack detection, attack detection time, packet loss ratio,
power consumption and average residual energy of RPL networks in IoT devices. With the utilization of
proposed firefly optimization technique, the network achieved better results compared to the existing
methods.
3.1.1. Attack detection
An exact and accurate detection of a black hole attack at any given time in the network is known as
attack detection. The comparison of black hole detection is represented in Figure 2 with the existing methods
MRTS and C Trust-RPL. Both methods detected many malicious nodes in the initial stage since there were
more malicious entities as shown in Figure 2. The no. of malicious nodes gradually becomes low once the
node trust was fully achieved. It is because of the proactive nature of RPL networks, adversary nodes were
eliminated from the network topology and alternative routes were discovered before the network gets
completely drained. The representation of attack detection in two existing methods MRTS and C Trust-RPL
are given in Table 2.
Figure 2. Attack detection
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Table 2. Comparison of trust-based RPL mechanism for attack detection of malicious nodes
Malicious nodes Attack detection
MRTS [26] C Trust-RPL[27] Proposed trust mechanism
1 348 380 410
2 205 252 275
3 235 240 287
4 205 252 300
5 90 140 185
6 90 140 190
7 89 140 178
8 99 145 175
9 85 130 155
10 90 140 184
3.1.2. Attack detection time
The efficiency of the proposed model in detecting attacks in less time is compared with the existing
methods of MRTS and C Trust-RPL. Figure 3 shows the graphical representation of attack detection time
compared to the proposed modified firefly algorithm. Initially, for one malicious node, the attack detection
time is shown and then increased one by one in order. In Figure 3, the second node detection keeps
increasing in proportion to the increase in the number of attacks. However, the proposed optimization
technique shows less time in attack detection compared to the existing methods. Table 3 shows a comparison
of trust-based RPL mechanisms for attack detection time.
Figure 3. Attack detection time
Table 3. Comparison of trust based RPL mechanism for attack detection time
Number of Attacks Attack detection time (seconds)
MRTS [26] C Trust-RPL [27] Proposed trust mechanism
1 0 0 0
2 3 2 1
3 4 4 2
4 5 5 2
5 8 6 4
6 0 6 4
7 11 9 5
8 12 10 7
9 15 11 8
10 18 14 8
3.1.3. Packet loss ratio
The ratio which depicts the lost packet to the total number of sent packets is known as the packet
loss ratio and it is graphically represented in Figure 4. Figure 4 shows the comparison of existing methods'
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packet loss ratio to the proposed method. The existing methods MRTS and C Trust-RPL are compared with
the proposed trust based privacy access control mechanism. The packet loss ratio pf the proposed framework
is less compared to the existing methods even under the same network parameters. Due to the similar
parameters, some of the patterns look natural for both frameworks. On average, the packet loss ratio for the
proposed framework at node 10 is 0.32, 0.49 for MRTS [26], and 0.39 for C Trust RPL [27]. Thus, the
proposed framework has given a better defense mechanism against black hole attacks with less packet loss
ratio. Table 4 shows the comparison of trust based RPL mechanism for packet loss ratio.
Figure 4. Packet loss ratio
Table 4. Comparison of trust based RPL mechanism for packet loss ratio
Number of Nodes Packet loss ratio (%)
MRTS [26] C Trust-RPL [27] Proposed trust mechanism
1 0.5 0.4 0.40
2 0.5 0.4 0.33
3 0.51 0.42 0.41
4 0.52 0.43 0.34
5 0.49 0.38 0.29
6 0.49 0.38 0.31
7 0.48 0.36 0.32
8 0.49 0.39 0.32
9 0.5 0.41 0.32
10 0.49 0.39 0.32
3.1.4. Power consumption
The proposed trust based mechanism achieved less power consumption compared to the existing
methods MRTS and C Trust-RPL. The power consumption for the existing methods is very high when
compared to the proposed optimization method as the existing methods do not have a mechanism for attack
mitigation to deal with the packet drops caused by malicious nodes in the network. As the proposed method
have an attached mitigation mechanism, the power consumption is less. Figure 5 shows the graphical
representation of the power consumption of the proposed method in comparison to the existing methods.
Table 5 represents power consumption values for the 10 nodes in the network.
3.1.5. Average residual energy
The node’s average residual energy in the network is saved with the proposed mechanism during
the simulation. With the proposed trust mechanism with privacy access control, the RPL network achieved
high residual energy compared to the existing methods MRTS and C Trust-RPL. The average residual
energy of the proposed method is 0.87 mJoules and the existing methods MRTS and C Trust-RPL are
0.3 and 0.7 mJ. Table 6 shows the average residual energy values and its graphical representation is shown
in Figure 6.
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Figure 5. Power consumption
Table 5. Comparison of trust based RPL mechanism for power consumption
Number of Nodes Power consumption
MRTS [26] C Trust-RPL [27] Proposed trust mechanism
1 0.55 0.5 0.43
2 0.73 0.5 0.48
3 0.7 0.51 0.51
4 0.6 0.52 0.45
5 0.52 0.49 0.45
6 0.75 0.49 0.46
7 0.6 0.48 0.39
8 0.52 0.49 0.44
9 0.65 0.5 0.41
10 0.75 0.49 0.39
Table 6. Comparison of trust based RPL mechanism for Average residual energy
Time (minutes) Average residual energy (mJoules)
MRTS [26] C Trust-RPL [27] Proposed trust mechanism
1 1 1 1
2 0.99 0.99 1
3 0.94 0.98 0.99
4 0.91 0.97 0.99
5 0.88 0.96 0.97
6 0.85 0.95 0.97
7 0.82 0.94 1.02
8 0.8 0.93 0.93
9 0.72 0.92 0.98
10 0.77 0.91 0.99
3.2. Discussion
From the results, it is analysed that the proposed method has the capability of providing
authentication in IoT devices by using key agreement protocol. Trust evaluation, privacy preserving and
energy consumption of nodes are problem in existing secure RPL protocols. Proposed method has the
authentication mechansim for trust evaluation, key based agreement for privacy preserving and due to
reduced redundancy energy consumption also reduced further. From the comparison with the existing
methods, MRTS [26] has limitations such as movement, and have its services tested towards different trust
thresholds. The C Trust-RPL [27] has a limitation of low scalability-based approach in terms of trust
parameters. These limitations are overcome by adding more scalable trust parameters in the network of IoT
devices. Even though, the proposed approach has contributed to develop the energy efficient and secure
routing in IoT devices, it still has ramifications such as prevention of black holes and data loss. The future
work focuses of preventing and mitigating black hole attacks and data loss before occurring in the network.
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Figure 6. Average residual energy
4. CONCLUSION
An energy-efficient, trust based interoperability framework for identifying and isolating black hole
attacks is included in the proposed RPL routing protocol. To preserve the limited IoT devices' energy, a
control layer computed the trust values. Using the privacy access control to observe the exchange of packets
between the nodes, it was possible to identify and remove nodes that are malicious in the network. According
to the results obtained after simulation, the proposed method performs better than MRTS and C Trust-RPL in
terms of attack detection time, power consumption, and average residual energy. The proposed mechanism
used 35% less energy and had a lower average packet loss ratio difference. However, the proposed
mechanism supports a huge number of devices such as RPL which are interconnected. In the future, research
will concentrate on improving more scalable and distributed trust-based mechanisms to satisfy the increasing
demands of distributive IoT deployments, as well as addressing other attacks in RPL networks, such as
selective forwarding attacks, rank, and black holes. Future research focuses on developing a lightweight
communication to secure data against disruptions in data transmission.
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BIOGRAPHIES OF AUTHORS
Shashikala Narayanappa received M. Tech degree in computer science and
engineering from VTU, Belagavi, India in 2013. I am currently pursuing Ph.D. degree in VTU,
Belagavi, India. My research interest includes internet of things, wireless sensor networks, and
security. Her membership in professional bodies is: life time membership in MIE, IEEE, CSI,
CRSI. She can be contacted at email: Shashikalan2006@gmail.com.
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Tulavanur Narayanareddy Anitha has 24 years teaching and research
experience in the field of computer science and engineering and served in different colleges
since 1997. Currently She is serving as Professor and HOD in the Department of Computer
Science and Engineering, Sir M. Visvesvaraya Institute of Technology, Bangalore, Karnataka.
She was awarded Ph.D. degree in “an efficient and scalable dynamic load balancing using
multi parameters on load aware distributed multi cluster servers” by Visveswaraiah
Technological University, Belagavi in 2016. She is s appointed as Referee for Ph.D.
examination at the Visveswaraiah Technological University and Reva University, Bangalore
March 2017. She has received recognition as GUIDE for Ph.D. program under computer
science and engineering from VTU, in January. 2017. She has published 40 research papers in
reputed international and Indian research journals in UGC Care Group – I and Group –II lists
under SCOPUS and other Journals, Google Scholar and has been a part of various workshops
and seminars conducted all over Karnataka. She has a life membership on CSI, ISTE, FIE and
IFERP. She is a member of board of examiner in Visveswaraiah Technological University. She
has been invited as speaker/resource person/subject expert at Faculty/Session Chair for
international conference at various Engineering Colleges in Karnataka. She is been invited as
External Examiner for Theory & Practical Examinations at various Engineering Colleges in
Karnataka associated with various universities such as Reva University, Visveswaraiah
Technological University, Autonomous University. She is an active member of advisory board,
editorial board member of international research journals of India, Springer and IJCS. She has
supervised many graduates, post-graduate students and research scholars for the research and
projects fulfilment of their degree program. She has published book chapters in
national/international books. Dr. T N Anitha has received Best Researcher awards from I2OR
and Green ThinkerZ. She can be contacted at email: Anithareddytn72@gmail.com.
Priti Mishra earned a bachelor's degree in information science and engineering
from SRSIT College of Engineering in Bangalore, which is affiliated with VTU. MVJ College
of Engineering, affiliated to VTU, Bangalore, and Maharaj Vinayak Global University, Jaipur,
respectively, with a PG in computer science & engineering and a Ph. D in computer science,
with a focus on network security. She's been a teacher for the past 18 years. She has authored
several books and published paper in national and international journals and has presented
papers in international and national conferences. There are 2 scholars who have been awarded
under her guidance. She is currently employed in East West College of Engineering,
Bangalore, as a professor and HOD in the Department of Computer Science and Engineering.
She can be contacted at email: mprits@redifmail.com.
Renuka Patil Herakal is working as an Asst. Professor in Department of
Computer Science and Engineering at GITAM (Deemed to be) University, Bangalore,
Karnataka, INDIA. She has completed M. Tech (CSE) under VTU in the year 2013 and Ph. D.
under VTU in the field of WSN and AI & ML. She has an experience of 13 years in teaching.
She has published 13 papers in international journals and 4 papers in international conference.
Her areas of interest are wireless sensor networks, artificial intelligence, machine learning,
cloud computing and natural language processing. She can be contacted at email:
rherakal@gitam.edu.
Jayasudha Kolur has 20 years teaching experience in various colleges since
1998. Currently She is serving as “Associate Professor” in Atria Institute of Technology,
Bangalore, and Karnataka. She was awarded Ph.D. degree in “Development of Multilayer Soft
Tissue Model for Applications in Virtual Surgery” by Visvesvaraya Technological University,
Belagavi in 2021. She has published various research papers in reputed international research
journals, also in UGC Care Group – I and Group-II lists under Scopus journals, Google
Scholar and has been a part of various workshops, seminars and Faculty Development
Programs attended and conducted. She has published book and book chapters in national/
international books. She has one patent filed and published. Her membership in professional
bodies is: life time membership in ISTE, CSI, CRSI and professional membership in IFERP
(Institute for Engineering Research and Publication). She can be contacted at email:
jayasudhakaiml@skit.org.in.