SlideShare une entreprise Scribd logo
1  sur  6
Télécharger pour lire hors ligne
International Journal of Computer Engineering and Technology (IJCET), ISSN 0976INTERNATIONAL JOURNAL OF COMPUTER ENGINEERING &
6367(Print), ISSN 0976 - 6375(Online), Volume 5, Issue 1, January (2014), © IAEME

TECHNOLOGY (IJCET)

ISSN 0976 – 6367(Print)
ISSN 0976 – 6375(Online)
Volume 5, Issue 1, January (2014), pp. 112-117
© IAEME: www.iaeme.com/ijcet.asp
Journal Impact Factor (2013): 6.1302 (Calculated by GISI)
www.jifactor.com

IJCET
©IAEME

ROBUST CAMPUS WIDE NETWORK DEFENDER
Archana D Wankhade1, Dr. P. N. Chatur2
1

2

Assistant Professor in information Technology Department, GCOE, Amravati, India
Head and Professor in Computer Science and Engineering Department, GCOE, Amravati, India.

ABSTRACT
The proposed software architecture is implemented by using agile software development
process. The proposed software for the defence against attacks deals with the attack generation,
attack detection in the intranet and then prevention of attacks. Attack prevention module is flexible
as we can add the rule in the firewall to prevent the any known attack. Due to space problem we
considered two attacks on every packet such as ICMP, UDP and TCP packet.
Keywords: Smurf, Ping of Death, ICMP Flood, LAND, XMAS, TCP Flood, Ping Pong Attack
Generation, Firewall Rules.
1. INTRODUCTION
Nations without controlled borders cannot ensure the security and safety of their citizens, nor
can they prevent privacy and theft. Similarly, networks without controlled access cannot ensure the
security or privacy of stored data, nor can they keep network resources from being exploited by
hackers. When internal network is connected to the internet, there is no inherent central point of
security control; in fact there is no security at all. Network security is one of the major considerations
in computer networking. Various types of tools are being used for providing security to networks.
Firewall and Intrusion Detection System are majors among them. We start with description of
firewall, types of firewall, comparison between firewalls, followed by algorithms used in our system.
Then we will cover IDS part of our system followed by algorithms. Lastly we see programming
languages and tools to be used in our system. Security consists of mechanisms for providing
confidentiality, integrity, and availability. Confidentiality means that only the individuals allowed
access to particular information should be able to access that information. Integrity refers to those
controls that prevent information from being altered in any unauthorized manner. Availability
controls are those that prevent the proper functioning of computer systems from being interfered
112
International Journal of Computer Engineering and Technology (IJCET), ISSN 09766367(Print), ISSN 0976 - 6375(Online), Volume 5, Issue 1, January (2014), © IAEME
with. As mentioned in computer network, security of data from network attacks is a major concern
area. In most networks firewalls are used as filter to prevent unwanted entry into private network.
Firewall is dedicated to only one thing – Deciding between authorized and unauthorized
communications. But still firewall cannot detect attacks on network. But IDS has its own limitations.
So we try to integrate them in such a way that to get best out of them.
2. LITERATURE SURVEY
2.1 Firewall
Firewall is dedicated to only one thing – Deciding between authorized and unauthorized
communications. This prevents having to make compromises between security, usability and
functionality. Without a firewall, systems are left to their own security devices and configurations.
The firewall is a single point of contact between untrusted networks. In general, firewalls mitigate
the risk that system will use for unauthorized or unintended purposes. There are three primary
attributes that are protected by a firewalls.
•

Risk to confidentiality

•

Risk to data integrity

•

Risk to availability

Most common usage of a firewall is between the internet connection and the local area
network. Other common firewall usages include protecting connections to external third parties, such
as market data providers, and between sensitive areas of an internal network.
2.2 How Firewall Works
A firewall is a software program or device that monitors, and sometimes controls, all
transmissions between an organization's internal network and the Internet. However large the
network, a firewall is typically deployed on the network's edge to prevent inappropriate access to
data behind the firewall. The firewall ensures that all communication in both directions conforms to
an organization's security policy. Firewall technologies are configurable. You can limit
communication by direction, IP address, protocol, ports, or numerous other combinations. If you
have access to the firewall, you can configure it to enable the ports, protocols, and addresses. In
some cases, however, your organization's security policy may prevent optimal streaming. For
example, firewalls configured to only allow TCP traffic may cause the user to see frequent buffering
of clips. User experience of the presentation is compromised; greater latency and start up times affect
the time needed to view the clip, and delivery of the clip requires more total bandwidth.
There are three techniques used for detection
•

Anomaly detection (behaviour based)

•

Misuse detection or Signature detection (knowledge based)

•

State full protocol analysis

113
International Journal of Computer Engineering and Technology (IJCET), ISSN 0976
09766367(Print), ISSN 0976 - 6375(Online), Volume 5, Issue 1, January (2014), © IAEME

Figure 1.1 Detection Capabilities of Different Intrusion Detection Model
Above Figure 1.1 shows detection capabilities of legal and illegal activities, it is misuse for
knowledge based and behaviour-based systems.
based
Anomaly detection: Anomaly detection is describes abnormal patterns behaviour, where
“abnormal” patterns it is defined beforehand. Anomaly based models are supposed to describe only
legal activities. and Also in this case, incompleteness and inaccuracy can false positive and false
negatives. Anomaly-based detection is process of comparing definitions of what activity is
based
considered normal against observed events to identify significant deviations. An IDPS using
ormal
anomaly-based detection has profiles that represent the normal behaviour of such things as users,
based
hosts, network connections, or applications. The profiles are developed by mon
monitoring the
characteristics of typical activity over a period of time. Following tables are shown comparison of
firewalls. Table 1.1 Comparison of firewalls.

114
International Journal of Computer Engineering and Technology (IJCET), ISSN 09766367(Print), ISSN 0976 - 6375(Online), Volume 5, Issue 1, January (2014), © IAEME
3. PROPOSED INTRUSION PREVENTION SYSTEM
Due to space problems, we have considered very few attacks and their defence mechanisms.
The implementation of proposed system is divided into following process: Attack Generation
algorithms, Defence Against Attack (Attack Prevention algorithms), Attack Detection Algorithms.
Some of the sample attack detection and prevention rules are discussed below:
3.1 Attack Generation algorithms
Packet Capture: We o used TCP dump and window dump to capture the incoming flow of
information and analysed this traffic by using the proposed IDS. Attack Generation Process can use
different tools like NMAP, Nessus, hping3 and Scapy to generate different kinds of trailer made
packet to do the attack. For Attack Generation we used the following tools
Scapy(http://www.scapy.org),Nmap(http://www.nmap.org),Hping3http://www.hping.org)
3.1.1 Land Attack Generation: #hping3 –a –spoof -flood <src_ip> <dst_ip> where a:spoof source
address src_ip : source ip address which is spoofed dst_ip : destination ip address
3.1.2 XMAS Attack Generation:
Using the Hping #hping3 –c 1 –V –p 80 –s 5050 –M 0 –UPF 192.16.0.103 Where c: count
V: command line switch for addition information about the packet
p : port no , s: source port, M: set the sequence
3.1.3 SYN Flood Attack Generation
Using the command: hping3 –S –fast –a <src_ip> <dest_ip>
where S : SYN packets are generated
fast : 10 packets per second
a:for spoofing option
src_ip : is a Source ip
3.1.4 XMAS Attack Generation
Using Scapy #hping3 –c 1 –V –p 80 –s 5050 –M 0 –UPF 192.16.0.103 Where: src :source ip,
dst :destination ip
flags : FPU-FIN,PUSH,URGENT
count : no of packet to generate.
3.2 Attack Detection Algorithms
Attack detection task will be carried out through
SnortIDSwww.snort.org),SPADE(www.silicondefence.com/Spice_JCS.pdf,www.silicondefense.org)
,NIDES(www.nides.org),HONEYPOT(www.Honeydpot.org),KESENSOR(www.keyfocus.net/kfsen
sor),HONEYD(www.Honeyd.org),TRIPWIRE(www.tripwire.org)
3.2.1 ICMP Attacks Detection: If protocol: ICMP and tyop: Request check if state[ipaddress] :
active else if state[ipaddress] :active and returncheck if lastpacket.time < 1 [1in 1sec]
count[ipaddress]++ else cout[ipaddress] : 0 if count[ipaddress] > 25 [70 in 1sec] reset
count[ipaddress]:0 and lastpacket.time :0 set alarm flag.
3.2.2 Smurf attack Detection: Alert icmp $External_net any : $home_net any (msg:”icmp smurf
attack detected”; dsize:4; icmp_id:0 ;icmp_seq:0 ; itype:8 ; classtype: attempted – recon ;
sid:78787878; )
115
International Journal of Computer Engineering and Technology (IJCET), ISSN 09766367(Print), ISSN 0976 - 6375(Online), Volume 5, Issue 1, January (2014), © IAEME
3.2.3 SYN Flood Attack Detection: If protocol: TCP and Type: Syn check if state[ipaddress] :
active else if state[ipaddress] : active and return
check if lastpacket.time < 1 [1in 1sec] count[ipaddress]++
else cout[ipaddress] : 0 if count[ipaddress] > 25 [70 in 1sec]
reset count[ipaddress]:0 and lastpacket.time :0
set alarm flag
3.2.4 LAND Attack Detection
If protocol: TCP and type: SYN,
if Sourceip port == Destination port ,
if Sourceip ip : Destination ip, set alarm flag
Udp Attacks
3.2.5 XMAS Attack Detection: Alert tcp any any : any any (msg: “X mas attack detected” flow:
stateless; flags: FPU,12; sid: 1234556;)
3.2.6 Fraggle Attack Detection: alert udp $EXTERNAL_NET any: $HOME_NET any
(msg:"UDP_Flood Attack!!!!!"; content:"UDP Flood Test"; flow:stateless; threshold:type threshold,
track .
4. CONCLUSIONS
Critical literature survey is made in order to carry this work. Enterprise’s general purpose
Application firewall / IDS evolved in way that has created conundrum for security. So, prime goal is
provide emerging solution which gives hybrid functionality of IDS, IPS, and Firewalls functionality
in single box which would be practical and easy to maintain. We have studied various packet
generation tools such as Nmap, Nessus, hping3 and Scapy. Then we have made experimentation for
the detection of attacks using the open source tools such as snort IDS, NIDES, HONEYPOT
KESENSOR, HONEYD, TRIPWIRE, and then we run the various firewalls such as iptable/Netfilter,
fwSnort Squid, CCProxy, Kerio.
REFERENCES
[1]
[2]
[3]
[4]

[5]

[6]
[7]

Intrusion detection system using Sax 2.0 and wire shark 1.2.2.
Shaw n Conaway, “Using an Intrusion Prevention System as Part of a Layered Security
Approach”, Network Support, Technical Enterprises, October-2006.
Ido green, tzvi raz, moshe zviran, “analysis of active intrusion prevention data for predicting
hostile activity in computer networks”, communications of the acm april 2007/vol. 50, no. 4.
suresh n. chari and pau-chen cheng, “BlueBoX: A Policy-Driven, Host-Based Intrusion
Detection System”, ACM Transactions on Information and System Security, Vol. 6, No. 2,
May 2003.
Nong Ye, Senior Member, IEEE, Syed Masum Emran, Qiang Chen, and Sean Vilbert(2002),
“Multivariate Statistical Analysis of Audit Trails for Host-Based Intrusion Detection”, ieee
transactions on computers, vol. 51, no. 7, july 2002.
Fang Yu, T. V. Lakshman, Randy H. Katz (2006), “Efficient Multimatch Packet
Classification for Network Security Applications”, ieee journal on selected areas in
communications, vol. 24, no. 10, october 2006.
Jianchao Han, Mohsen Beheshti, Kazimierz Kowalski, Joel Ortiz, Johnly Tomelden,
“Component-based Software Architecture Design for Network Intrusion Detection and
Prevention System”, IEEE Computer society Sixth International Conference on Information
Technology: New Generations 2009.
116
International Journal of Computer Engineering and Technology (IJCET), ISSN 09766367(Print), ISSN 0976 - 6375(Online), Volume 5, Issue 1, January (2014), © IAEME
[8]

[9]
[10]
[11]

[12]
[13]
[14]

[15]

[16]
[17]

[18]
[20]
[21]

[21]

[22]

[23]

[24]
[25]
[26]

david j., chaboya, richard a. raines, rusty o. aldwin, and barry e. mullins,”Network ntrusion
etection Automated and Manual Methods Prone to Attack and Evasion”, published by the
ieee computer society, 2006.
Jiong Zhang, Mohammad Zulkernine, and Anwar Haque(2008), “Random-Forests-Based
Network Intrusion Detection Systems”.
Catherine Paquet “Network security using Cisco IDS IPS”, Pearson Education intrusion
detection system using Sax 2.0 and wireshark 1.2.2.
Nong Ye, Senior Member, IEEE, Syed Masum Emran, Qiang Chen, and Sean Vilbert(2002),
“Multivariate Statistical Analysis of Audit Trails for Host-Based Intrusion Detection”, ieee
transactions on computers, vol. 51, no. 7, july 2002.
George Lawton, “Open Source Security: Opportunity or Oxymoron?” March 2002.
K. Salah A. Kahtani(2009), “Improving Snort performance under Linux”, IET Commun.,
2009, Vol. 3, Issue. 12.
Fang Yu, T. V. Lakshman, Randy H. Katz (2006), “Efficient Multimatch Packet
Classification for Network Security Applications”, ieee journal on selected areas in
communications, vol. 24, no. 10, october 2006.
Jianchao Han, Mohsen Beheshti, Kazimierz Kowalski, Joel Ortiz, Johnly
TomeldenComponentbased Software Architecture Design for Network Intrusion Detection
and Prevention System, 2009 IEEE Computer society Sixth International Conference on
Information Technology: New Generations 2009.
Hui Li, Dihua Liu, “Research on Intelligent Intrusion Prevention System Based on Snort”,
International Conference on Computer, Mechatronics, Control and Electronic Engineering
(CMCE) 2010.
Snort Manual and Whitepapers on Rule Optimization, Detection, High-performance multi
rule detection engine, Protocol Flow analyzer. All available at the Snort homepage:
http://www.sourcefire.com/products/library.html.
Jiong Zhang, Mohammad Zulkernine, and Anwar Haque(2008), “Random-Forests-Based
Network Intrusion Detection Systems”, vol. 38, no. 5, september 2008.
SNORT R Users Manual 2.9.1.
Anna Sperotto, Gregor Schaffrath, Ramin Sadre, Cristian Morariu, Aiko Pras and Burkhard
Stiller (2010)”An Overview of IP Flow-Based Intrusion Detection”, ieee communications
surveys & tutorials, vol. 12, no. 3, third quarter 2010.
P.Vigneshwaran and Dr. R. Dhanasekaran, “A Novel Protocol To Improve TCP Performance
– Proposal”, International Journal of Computer Engineering & Technology (IJCET), Volume
3, Issue 2, 2012, pp. 372 - 377, ISSN Print: 0976 – 6367, ISSN Online: 0976 – 6375.
Kusum Nara and Aman Dureja, “A Dynamic Approach for Improving Performance of
Intrusion Detection System Over Manet”, International Journal of Computer Engineering &
Technology (IJCET), Volume 4, Issue 4, 2013, pp. 61 - 81, ISSN Print: 0976 – 6367,
ISSN Online: 0976 – 6375.
Syeda Gauhar Fatima, Dr. Syed Abdul Sattar and Dr.K.Anita Sheela, “Energy Efficient
Intrusion Detection System for WSN”, International Journal of Electronics and
Communication Engineering & Technology (IJECET), Volume 3, Issue 3, 2012,
pp. 246 - 250, ISSN Print: 0976- 6464, ISSN Online: 0976 –6472.
JPCAP online tutorial.
http://www.cert.org/advisories/CA-1996-01.html.
http://www.cert.org/advisories/CA-1996-26.html.

117

Contenu connexe

Tendances

An analysis of Network Intrusion Detection System using SNORT
An analysis of Network Intrusion Detection System using SNORTAn analysis of Network Intrusion Detection System using SNORT
An analysis of Network Intrusion Detection System using SNORTijsrd.com
 
TACTiCS_WP Security_Addressing Security in SDN Environment
TACTiCS_WP Security_Addressing Security in SDN EnvironmentTACTiCS_WP Security_Addressing Security in SDN Environment
TACTiCS_WP Security_Addressing Security in SDN EnvironmentSaikat Chaudhuri
 
Seminar Report - Network Intrusion Prevention by Configuring ACLs on the Rout...
Seminar Report - Network Intrusion Prevention by Configuring ACLs on the Rout...Seminar Report - Network Intrusion Prevention by Configuring ACLs on the Rout...
Seminar Report - Network Intrusion Prevention by Configuring ACLs on the Rout...Disha Bedi
 
Network Intrusion Prevention by Configuring ACLs on the Routers, based on Sno...
Network Intrusion Prevention by Configuring ACLs on the Routers, based on Sno...Network Intrusion Prevention by Configuring ACLs on the Routers, based on Sno...
Network Intrusion Prevention by Configuring ACLs on the Routers, based on Sno...Disha Bedi
 
Layered Approach for Preprocessing of Data in Intrusion Prevention Systems
Layered Approach for Preprocessing of Data in Intrusion Prevention SystemsLayered Approach for Preprocessing of Data in Intrusion Prevention Systems
Layered Approach for Preprocessing of Data in Intrusion Prevention SystemsEditor IJCATR
 
Wireless Networking
Wireless NetworkingWireless Networking
Wireless NetworkingGulshanAra14
 
Denial of Service Attack Defense Techniques
Denial of Service Attack Defense TechniquesDenial of Service Attack Defense Techniques
Denial of Service Attack Defense TechniquesIRJET Journal
 
Detection of Idle Stealth Port Scan Attack in Network Intrusion Detection Sys...
Detection of Idle Stealth Port Scan Attack in Network Intrusion Detection Sys...Detection of Idle Stealth Port Scan Attack in Network Intrusion Detection Sys...
Detection of Idle Stealth Port Scan Attack in Network Intrusion Detection Sys...skpatel91
 
Network intrusi detection system
Network intrusi detection systemNetwork intrusi detection system
Network intrusi detection systemDuwinowo NT
 
Using Genetic algorithm for Network Intrusion Detection
Using Genetic algorithm for Network Intrusion DetectionUsing Genetic algorithm for Network Intrusion Detection
Using Genetic algorithm for Network Intrusion DetectionSagar Uday Kumar
 
Ccna security prep from networkers
Ccna security prep from networkersCcna security prep from networkers
Ccna security prep from networkersIvana Veljkovic
 
Next Generation Network: Security and Architecture
Next Generation Network: Security and ArchitectureNext Generation Network: Security and Architecture
Next Generation Network: Security and Architectureijsrd.com
 
Update On The Cern. Computing And Network Infrastructure For Controls. (Cnic)...
Update On The Cern. Computing And Network Infrastructure For Controls. (Cnic)...Update On The Cern. Computing And Network Infrastructure For Controls. (Cnic)...
Update On The Cern. Computing And Network Infrastructure For Controls. (Cnic)...ESS BILBAO
 
3778975074 january march 2015 1
3778975074 january march 2015 13778975074 january march 2015 1
3778975074 january march 2015 1nicfs
 
Honeypot- An Overview
Honeypot- An OverviewHoneypot- An Overview
Honeypot- An OverviewIRJET Journal
 

Tendances (19)

35 38
35 3835 38
35 38
 
An analysis of Network Intrusion Detection System using SNORT
An analysis of Network Intrusion Detection System using SNORTAn analysis of Network Intrusion Detection System using SNORT
An analysis of Network Intrusion Detection System using SNORT
 
TACTiCS_WP Security_Addressing Security in SDN Environment
TACTiCS_WP Security_Addressing Security in SDN EnvironmentTACTiCS_WP Security_Addressing Security in SDN Environment
TACTiCS_WP Security_Addressing Security in SDN Environment
 
Seminar Report - Network Intrusion Prevention by Configuring ACLs on the Rout...
Seminar Report - Network Intrusion Prevention by Configuring ACLs on the Rout...Seminar Report - Network Intrusion Prevention by Configuring ACLs on the Rout...
Seminar Report - Network Intrusion Prevention by Configuring ACLs on the Rout...
 
Network Intrusion Prevention by Configuring ACLs on the Routers, based on Sno...
Network Intrusion Prevention by Configuring ACLs on the Routers, based on Sno...Network Intrusion Prevention by Configuring ACLs on the Routers, based on Sno...
Network Intrusion Prevention by Configuring ACLs on the Routers, based on Sno...
 
Layered Approach for Preprocessing of Data in Intrusion Prevention Systems
Layered Approach for Preprocessing of Data in Intrusion Prevention SystemsLayered Approach for Preprocessing of Data in Intrusion Prevention Systems
Layered Approach for Preprocessing of Data in Intrusion Prevention Systems
 
Security technology
Security technologySecurity technology
Security technology
 
Wireless Networking
Wireless NetworkingWireless Networking
Wireless Networking
 
Denial of Service Attack Defense Techniques
Denial of Service Attack Defense TechniquesDenial of Service Attack Defense Techniques
Denial of Service Attack Defense Techniques
 
Detection of Idle Stealth Port Scan Attack in Network Intrusion Detection Sys...
Detection of Idle Stealth Port Scan Attack in Network Intrusion Detection Sys...Detection of Idle Stealth Port Scan Attack in Network Intrusion Detection Sys...
Detection of Idle Stealth Port Scan Attack in Network Intrusion Detection Sys...
 
IDS and IPS
IDS and IPSIDS and IPS
IDS and IPS
 
Network intrusi detection system
Network intrusi detection systemNetwork intrusi detection system
Network intrusi detection system
 
Using Genetic algorithm for Network Intrusion Detection
Using Genetic algorithm for Network Intrusion DetectionUsing Genetic algorithm for Network Intrusion Detection
Using Genetic algorithm for Network Intrusion Detection
 
Ccna security prep from networkers
Ccna security prep from networkersCcna security prep from networkers
Ccna security prep from networkers
 
Next Generation Network: Security and Architecture
Next Generation Network: Security and ArchitectureNext Generation Network: Security and Architecture
Next Generation Network: Security and Architecture
 
Update On The Cern. Computing And Network Infrastructure For Controls. (Cnic)...
Update On The Cern. Computing And Network Infrastructure For Controls. (Cnic)...Update On The Cern. Computing And Network Infrastructure For Controls. (Cnic)...
Update On The Cern. Computing And Network Infrastructure For Controls. (Cnic)...
 
3778975074 january march 2015 1
3778975074 january march 2015 13778975074 january march 2015 1
3778975074 january march 2015 1
 
Honeypot- An Overview
Honeypot- An OverviewHoneypot- An Overview
Honeypot- An Overview
 
Ii2514901494
Ii2514901494Ii2514901494
Ii2514901494
 

En vedette

잡코리아 글로벌 프런티어 2기_지구인 이단 옆차기_탐방 보고서
잡코리아 글로벌 프런티어 2기_지구인 이단 옆차기_탐방 보고서잡코리아 글로벌 프런티어 2기_지구인 이단 옆차기_탐방 보고서
잡코리아 글로벌 프런티어 2기_지구인 이단 옆차기_탐방 보고서잡코리아 글로벌 프런티어
 
Hh News Bytes 0407
Hh News Bytes 0407Hh News Bytes 0407
Hh News Bytes 0407Ezra_Bettis
 
‘Over the Horizon’ sharemarket commentary – October 2013
‘Over the Horizon’ sharemarket commentary – October 2013‘Over the Horizon’ sharemarket commentary – October 2013
‘Over the Horizon’ sharemarket commentary – October 2013David Offer
 
Arduino experimenters guide hq
Arduino experimenters guide hqArduino experimenters guide hq
Arduino experimenters guide hqAndreis Santos
 
HOW WE ADVOCATED FOR INBOUND, UPSOLD ACCOUNTS, AND BUILT A BETTER ORGANIZATIO...
HOW WE ADVOCATED FOR INBOUND, UPSOLD ACCOUNTS, AND BUILT A BETTER ORGANIZATIO...HOW WE ADVOCATED FOR INBOUND, UPSOLD ACCOUNTS, AND BUILT A BETTER ORGANIZATIO...
HOW WE ADVOCATED FOR INBOUND, UPSOLD ACCOUNTS, AND BUILT A BETTER ORGANIZATIO...HubSpot
 

En vedette (9)

잡코리아 글로벌 프런티어 2기_지구인 이단 옆차기_탐방 보고서
잡코리아 글로벌 프런티어 2기_지구인 이단 옆차기_탐방 보고서잡코리아 글로벌 프런티어 2기_지구인 이단 옆차기_탐방 보고서
잡코리아 글로벌 프런티어 2기_지구인 이단 옆차기_탐방 보고서
 
Hh News Bytes 0407
Hh News Bytes 0407Hh News Bytes 0407
Hh News Bytes 0407
 
20320140502001
2032014050200120320140502001
20320140502001
 
50120140502001 2
50120140502001 250120140502001 2
50120140502001 2
 
20320140502002
2032014050200220320140502002
20320140502002
 
‘Over the Horizon’ sharemarket commentary – October 2013
‘Over the Horizon’ sharemarket commentary – October 2013‘Over the Horizon’ sharemarket commentary – October 2013
‘Over the Horizon’ sharemarket commentary – October 2013
 
Rules of Fasting
Rules of FastingRules of Fasting
Rules of Fasting
 
Arduino experimenters guide hq
Arduino experimenters guide hqArduino experimenters guide hq
Arduino experimenters guide hq
 
HOW WE ADVOCATED FOR INBOUND, UPSOLD ACCOUNTS, AND BUILT A BETTER ORGANIZATIO...
HOW WE ADVOCATED FOR INBOUND, UPSOLD ACCOUNTS, AND BUILT A BETTER ORGANIZATIO...HOW WE ADVOCATED FOR INBOUND, UPSOLD ACCOUNTS, AND BUILT A BETTER ORGANIZATIO...
HOW WE ADVOCATED FOR INBOUND, UPSOLD ACCOUNTS, AND BUILT A BETTER ORGANIZATIO...
 

Similaire à 50120140501013

DEFENSE MECHANISMS FOR COMPUTER-BASED INFORMATION SYSTEMS
DEFENSE MECHANISMS FOR COMPUTER-BASED INFORMATION SYSTEMSDEFENSE MECHANISMS FOR COMPUTER-BASED INFORMATION SYSTEMS
DEFENSE MECHANISMS FOR COMPUTER-BASED INFORMATION SYSTEMSIJNSA Journal
 
DEFENSE MECHANISMS FOR COMPUTER-BASED INFORMATION SYSTEMS
DEFENSE MECHANISMS FOR COMPUTER-BASED INFORMATION SYSTEMS DEFENSE MECHANISMS FOR COMPUTER-BASED INFORMATION SYSTEMS
DEFENSE MECHANISMS FOR COMPUTER-BASED INFORMATION SYSTEMS IJNSA Journal
 
STANDARDISATION AND CLASSIFICATION OF ALERTS GENERATED BY INTRUSION DETECTION...
STANDARDISATION AND CLASSIFICATION OF ALERTS GENERATED BY INTRUSION DETECTION...STANDARDISATION AND CLASSIFICATION OF ALERTS GENERATED BY INTRUSION DETECTION...
STANDARDISATION AND CLASSIFICATION OF ALERTS GENERATED BY INTRUSION DETECTION...IJCI JOURNAL
 
D03302030036
D03302030036D03302030036
D03302030036theijes
 
EFFICACY OF ATTACK DETECTION CAPABILITY OF IDPS BASED ON ITS DEPLOYMENT IN WI...
EFFICACY OF ATTACK DETECTION CAPABILITY OF IDPS BASED ON ITS DEPLOYMENT IN WI...EFFICACY OF ATTACK DETECTION CAPABILITY OF IDPS BASED ON ITS DEPLOYMENT IN WI...
EFFICACY OF ATTACK DETECTION CAPABILITY OF IDPS BASED ON ITS DEPLOYMENT IN WI...IJNSA Journal
 
Survey on classification techniques for intrusion detection
Survey on classification techniques for intrusion detectionSurvey on classification techniques for intrusion detection
Survey on classification techniques for intrusion detectioncsandit
 
INTRUSION DETECTION SYSTEM USING CUSTOMIZED RULES FOR SNORT
INTRUSION DETECTION SYSTEM USING CUSTOMIZED RULES FOR SNORTINTRUSION DETECTION SYSTEM USING CUSTOMIZED RULES FOR SNORT
INTRUSION DETECTION SYSTEM USING CUSTOMIZED RULES FOR SNORTIJMIT JOURNAL
 
Implementing a Robust Network-Based Intrusion Detection System
Implementing a Robust Network-Based Intrusion Detection SystemImplementing a Robust Network-Based Intrusion Detection System
Implementing a Robust Network-Based Intrusion Detection Systemtheijes
 
IMPROVED IDS USING LAYERED CRFS WITH LOGON RESTRICTIONS AND MOBILE ALERTS BAS...
IMPROVED IDS USING LAYERED CRFS WITH LOGON RESTRICTIONS AND MOBILE ALERTS BAS...IMPROVED IDS USING LAYERED CRFS WITH LOGON RESTRICTIONS AND MOBILE ALERTS BAS...
IMPROVED IDS USING LAYERED CRFS WITH LOGON RESTRICTIONS AND MOBILE ALERTS BAS...IJNSA Journal
 
SIP Flooding Attack Detection Using Hybrid Detection Algorithm
SIP Flooding Attack Detection Using Hybrid Detection AlgorithmSIP Flooding Attack Detection Using Hybrid Detection Algorithm
SIP Flooding Attack Detection Using Hybrid Detection AlgorithmEditor IJMTER
 
Certified Ethical Hacking
Certified Ethical HackingCertified Ethical Hacking
Certified Ethical HackingJennifer Wood
 
A honeynet framework to promote enterprise network security
A honeynet framework to promote enterprise network securityA honeynet framework to promote enterprise network security
A honeynet framework to promote enterprise network securityIAEME Publication
 
DYNAMIC IDP SIGNATURE PROCESSING BY FAST ELIMINATION USING DFA
DYNAMIC IDP SIGNATURE PROCESSING BY FAST ELIMINATION USING DFADYNAMIC IDP SIGNATURE PROCESSING BY FAST ELIMINATION USING DFA
DYNAMIC IDP SIGNATURE PROCESSING BY FAST ELIMINATION USING DFAIJNSA Journal
 
DEPLOYMENT OF INTRUSION PREVENTION SYSTEM ON MULTI-CORE PROCESSOR BASED SECUR...
DEPLOYMENT OF INTRUSION PREVENTION SYSTEM ON MULTI-CORE PROCESSOR BASED SECUR...DEPLOYMENT OF INTRUSION PREVENTION SYSTEM ON MULTI-CORE PROCESSOR BASED SECUR...
DEPLOYMENT OF INTRUSION PREVENTION SYSTEM ON MULTI-CORE PROCESSOR BASED SECUR...IJCNCJournal
 
Dismantling intrusion prevention_systems
Dismantling intrusion prevention_systemsDismantling intrusion prevention_systems
Dismantling intrusion prevention_systemsOlli-Pekka Niemi
 

Similaire à 50120140501013 (20)

DEFENSE MECHANISMS FOR COMPUTER-BASED INFORMATION SYSTEMS
DEFENSE MECHANISMS FOR COMPUTER-BASED INFORMATION SYSTEMSDEFENSE MECHANISMS FOR COMPUTER-BASED INFORMATION SYSTEMS
DEFENSE MECHANISMS FOR COMPUTER-BASED INFORMATION SYSTEMS
 
DEFENSE MECHANISMS FOR COMPUTER-BASED INFORMATION SYSTEMS
DEFENSE MECHANISMS FOR COMPUTER-BASED INFORMATION SYSTEMS DEFENSE MECHANISMS FOR COMPUTER-BASED INFORMATION SYSTEMS
DEFENSE MECHANISMS FOR COMPUTER-BASED INFORMATION SYSTEMS
 
1776 1779
1776 17791776 1779
1776 1779
 
1776 1779
1776 17791776 1779
1776 1779
 
STANDARDISATION AND CLASSIFICATION OF ALERTS GENERATED BY INTRUSION DETECTION...
STANDARDISATION AND CLASSIFICATION OF ALERTS GENERATED BY INTRUSION DETECTION...STANDARDISATION AND CLASSIFICATION OF ALERTS GENERATED BY INTRUSION DETECTION...
STANDARDISATION AND CLASSIFICATION OF ALERTS GENERATED BY INTRUSION DETECTION...
 
Ijnsa050214
Ijnsa050214Ijnsa050214
Ijnsa050214
 
D03302030036
D03302030036D03302030036
D03302030036
 
EFFICACY OF ATTACK DETECTION CAPABILITY OF IDPS BASED ON ITS DEPLOYMENT IN WI...
EFFICACY OF ATTACK DETECTION CAPABILITY OF IDPS BASED ON ITS DEPLOYMENT IN WI...EFFICACY OF ATTACK DETECTION CAPABILITY OF IDPS BASED ON ITS DEPLOYMENT IN WI...
EFFICACY OF ATTACK DETECTION CAPABILITY OF IDPS BASED ON ITS DEPLOYMENT IN WI...
 
Survey on classification techniques for intrusion detection
Survey on classification techniques for intrusion detectionSurvey on classification techniques for intrusion detection
Survey on classification techniques for intrusion detection
 
INTRUSION DETECTION SYSTEM USING CUSTOMIZED RULES FOR SNORT
INTRUSION DETECTION SYSTEM USING CUSTOMIZED RULES FOR SNORTINTRUSION DETECTION SYSTEM USING CUSTOMIZED RULES FOR SNORT
INTRUSION DETECTION SYSTEM USING CUSTOMIZED RULES FOR SNORT
 
Implementing a Robust Network-Based Intrusion Detection System
Implementing a Robust Network-Based Intrusion Detection SystemImplementing a Robust Network-Based Intrusion Detection System
Implementing a Robust Network-Based Intrusion Detection System
 
IMPROVED IDS USING LAYERED CRFS WITH LOGON RESTRICTIONS AND MOBILE ALERTS BAS...
IMPROVED IDS USING LAYERED CRFS WITH LOGON RESTRICTIONS AND MOBILE ALERTS BAS...IMPROVED IDS USING LAYERED CRFS WITH LOGON RESTRICTIONS AND MOBILE ALERTS BAS...
IMPROVED IDS USING LAYERED CRFS WITH LOGON RESTRICTIONS AND MOBILE ALERTS BAS...
 
SIP Flooding Attack Detection Using Hybrid Detection Algorithm
SIP Flooding Attack Detection Using Hybrid Detection AlgorithmSIP Flooding Attack Detection Using Hybrid Detection Algorithm
SIP Flooding Attack Detection Using Hybrid Detection Algorithm
 
Certified Ethical Hacking
Certified Ethical HackingCertified Ethical Hacking
Certified Ethical Hacking
 
Es34887891
Es34887891Es34887891
Es34887891
 
A honeynet framework to promote enterprise network security
A honeynet framework to promote enterprise network securityA honeynet framework to promote enterprise network security
A honeynet framework to promote enterprise network security
 
DYNAMIC IDP SIGNATURE PROCESSING BY FAST ELIMINATION USING DFA
DYNAMIC IDP SIGNATURE PROCESSING BY FAST ELIMINATION USING DFADYNAMIC IDP SIGNATURE PROCESSING BY FAST ELIMINATION USING DFA
DYNAMIC IDP SIGNATURE PROCESSING BY FAST ELIMINATION USING DFA
 
DEPLOYMENT OF INTRUSION PREVENTION SYSTEM ON MULTI-CORE PROCESSOR BASED SECUR...
DEPLOYMENT OF INTRUSION PREVENTION SYSTEM ON MULTI-CORE PROCESSOR BASED SECUR...DEPLOYMENT OF INTRUSION PREVENTION SYSTEM ON MULTI-CORE PROCESSOR BASED SECUR...
DEPLOYMENT OF INTRUSION PREVENTION SYSTEM ON MULTI-CORE PROCESSOR BASED SECUR...
 
Dismantling intrusion prevention_systems
Dismantling intrusion prevention_systemsDismantling intrusion prevention_systems
Dismantling intrusion prevention_systems
 
50320130403001 2-3
50320130403001 2-350320130403001 2-3
50320130403001 2-3
 

Plus de IAEME Publication

IAEME_Publication_Call_for_Paper_September_2022.pdf
IAEME_Publication_Call_for_Paper_September_2022.pdfIAEME_Publication_Call_for_Paper_September_2022.pdf
IAEME_Publication_Call_for_Paper_September_2022.pdfIAEME Publication
 
MODELING AND ANALYSIS OF SURFACE ROUGHNESS AND WHITE LATER THICKNESS IN WIRE-...
MODELING AND ANALYSIS OF SURFACE ROUGHNESS AND WHITE LATER THICKNESS IN WIRE-...MODELING AND ANALYSIS OF SURFACE ROUGHNESS AND WHITE LATER THICKNESS IN WIRE-...
MODELING AND ANALYSIS OF SURFACE ROUGHNESS AND WHITE LATER THICKNESS IN WIRE-...IAEME Publication
 
A STUDY ON THE REASONS FOR TRANSGENDER TO BECOME ENTREPRENEURS
A STUDY ON THE REASONS FOR TRANSGENDER TO BECOME ENTREPRENEURSA STUDY ON THE REASONS FOR TRANSGENDER TO BECOME ENTREPRENEURS
A STUDY ON THE REASONS FOR TRANSGENDER TO BECOME ENTREPRENEURSIAEME Publication
 
BROAD UNEXPOSED SKILLS OF TRANSGENDER ENTREPRENEURS
BROAD UNEXPOSED SKILLS OF TRANSGENDER ENTREPRENEURSBROAD UNEXPOSED SKILLS OF TRANSGENDER ENTREPRENEURS
BROAD UNEXPOSED SKILLS OF TRANSGENDER ENTREPRENEURSIAEME Publication
 
DETERMINANTS AFFECTING THE USER'S INTENTION TO USE MOBILE BANKING APPLICATIONS
DETERMINANTS AFFECTING THE USER'S INTENTION TO USE MOBILE BANKING APPLICATIONSDETERMINANTS AFFECTING THE USER'S INTENTION TO USE MOBILE BANKING APPLICATIONS
DETERMINANTS AFFECTING THE USER'S INTENTION TO USE MOBILE BANKING APPLICATIONSIAEME Publication
 
ANALYSE THE USER PREDILECTION ON GPAY AND PHONEPE FOR DIGITAL TRANSACTIONS
ANALYSE THE USER PREDILECTION ON GPAY AND PHONEPE FOR DIGITAL TRANSACTIONSANALYSE THE USER PREDILECTION ON GPAY AND PHONEPE FOR DIGITAL TRANSACTIONS
ANALYSE THE USER PREDILECTION ON GPAY AND PHONEPE FOR DIGITAL TRANSACTIONSIAEME Publication
 
VOICE BASED ATM FOR VISUALLY IMPAIRED USING ARDUINO
VOICE BASED ATM FOR VISUALLY IMPAIRED USING ARDUINOVOICE BASED ATM FOR VISUALLY IMPAIRED USING ARDUINO
VOICE BASED ATM FOR VISUALLY IMPAIRED USING ARDUINOIAEME Publication
 
IMPACT OF EMOTIONAL INTELLIGENCE ON HUMAN RESOURCE MANAGEMENT PRACTICES AMONG...
IMPACT OF EMOTIONAL INTELLIGENCE ON HUMAN RESOURCE MANAGEMENT PRACTICES AMONG...IMPACT OF EMOTIONAL INTELLIGENCE ON HUMAN RESOURCE MANAGEMENT PRACTICES AMONG...
IMPACT OF EMOTIONAL INTELLIGENCE ON HUMAN RESOURCE MANAGEMENT PRACTICES AMONG...IAEME Publication
 
VISUALISING AGING PARENTS & THEIR CLOSE CARERS LIFE JOURNEY IN AGING ECONOMY
VISUALISING AGING PARENTS & THEIR CLOSE CARERS LIFE JOURNEY IN AGING ECONOMYVISUALISING AGING PARENTS & THEIR CLOSE CARERS LIFE JOURNEY IN AGING ECONOMY
VISUALISING AGING PARENTS & THEIR CLOSE CARERS LIFE JOURNEY IN AGING ECONOMYIAEME Publication
 
A STUDY ON THE IMPACT OF ORGANIZATIONAL CULTURE ON THE EFFECTIVENESS OF PERFO...
A STUDY ON THE IMPACT OF ORGANIZATIONAL CULTURE ON THE EFFECTIVENESS OF PERFO...A STUDY ON THE IMPACT OF ORGANIZATIONAL CULTURE ON THE EFFECTIVENESS OF PERFO...
A STUDY ON THE IMPACT OF ORGANIZATIONAL CULTURE ON THE EFFECTIVENESS OF PERFO...IAEME Publication
 
GANDHI ON NON-VIOLENT POLICE
GANDHI ON NON-VIOLENT POLICEGANDHI ON NON-VIOLENT POLICE
GANDHI ON NON-VIOLENT POLICEIAEME Publication
 
A STUDY ON TALENT MANAGEMENT AND ITS IMPACT ON EMPLOYEE RETENTION IN SELECTED...
A STUDY ON TALENT MANAGEMENT AND ITS IMPACT ON EMPLOYEE RETENTION IN SELECTED...A STUDY ON TALENT MANAGEMENT AND ITS IMPACT ON EMPLOYEE RETENTION IN SELECTED...
A STUDY ON TALENT MANAGEMENT AND ITS IMPACT ON EMPLOYEE RETENTION IN SELECTED...IAEME Publication
 
ATTRITION IN THE IT INDUSTRY DURING COVID-19 PANDEMIC: LINKING EMOTIONAL INTE...
ATTRITION IN THE IT INDUSTRY DURING COVID-19 PANDEMIC: LINKING EMOTIONAL INTE...ATTRITION IN THE IT INDUSTRY DURING COVID-19 PANDEMIC: LINKING EMOTIONAL INTE...
ATTRITION IN THE IT INDUSTRY DURING COVID-19 PANDEMIC: LINKING EMOTIONAL INTE...IAEME Publication
 
INFLUENCE OF TALENT MANAGEMENT PRACTICES ON ORGANIZATIONAL PERFORMANCE A STUD...
INFLUENCE OF TALENT MANAGEMENT PRACTICES ON ORGANIZATIONAL PERFORMANCE A STUD...INFLUENCE OF TALENT MANAGEMENT PRACTICES ON ORGANIZATIONAL PERFORMANCE A STUD...
INFLUENCE OF TALENT MANAGEMENT PRACTICES ON ORGANIZATIONAL PERFORMANCE A STUD...IAEME Publication
 
A STUDY OF VARIOUS TYPES OF LOANS OF SELECTED PUBLIC AND PRIVATE SECTOR BANKS...
A STUDY OF VARIOUS TYPES OF LOANS OF SELECTED PUBLIC AND PRIVATE SECTOR BANKS...A STUDY OF VARIOUS TYPES OF LOANS OF SELECTED PUBLIC AND PRIVATE SECTOR BANKS...
A STUDY OF VARIOUS TYPES OF LOANS OF SELECTED PUBLIC AND PRIVATE SECTOR BANKS...IAEME Publication
 
EXPERIMENTAL STUDY OF MECHANICAL AND TRIBOLOGICAL RELATION OF NYLON/BaSO4 POL...
EXPERIMENTAL STUDY OF MECHANICAL AND TRIBOLOGICAL RELATION OF NYLON/BaSO4 POL...EXPERIMENTAL STUDY OF MECHANICAL AND TRIBOLOGICAL RELATION OF NYLON/BaSO4 POL...
EXPERIMENTAL STUDY OF MECHANICAL AND TRIBOLOGICAL RELATION OF NYLON/BaSO4 POL...IAEME Publication
 
ROLE OF SOCIAL ENTREPRENEURSHIP IN RURAL DEVELOPMENT OF INDIA - PROBLEMS AND ...
ROLE OF SOCIAL ENTREPRENEURSHIP IN RURAL DEVELOPMENT OF INDIA - PROBLEMS AND ...ROLE OF SOCIAL ENTREPRENEURSHIP IN RURAL DEVELOPMENT OF INDIA - PROBLEMS AND ...
ROLE OF SOCIAL ENTREPRENEURSHIP IN RURAL DEVELOPMENT OF INDIA - PROBLEMS AND ...IAEME Publication
 
OPTIMAL RECONFIGURATION OF POWER DISTRIBUTION RADIAL NETWORK USING HYBRID MET...
OPTIMAL RECONFIGURATION OF POWER DISTRIBUTION RADIAL NETWORK USING HYBRID MET...OPTIMAL RECONFIGURATION OF POWER DISTRIBUTION RADIAL NETWORK USING HYBRID MET...
OPTIMAL RECONFIGURATION OF POWER DISTRIBUTION RADIAL NETWORK USING HYBRID MET...IAEME Publication
 
APPLICATION OF FRUGAL APPROACH FOR PRODUCTIVITY IMPROVEMENT - A CASE STUDY OF...
APPLICATION OF FRUGAL APPROACH FOR PRODUCTIVITY IMPROVEMENT - A CASE STUDY OF...APPLICATION OF FRUGAL APPROACH FOR PRODUCTIVITY IMPROVEMENT - A CASE STUDY OF...
APPLICATION OF FRUGAL APPROACH FOR PRODUCTIVITY IMPROVEMENT - A CASE STUDY OF...IAEME Publication
 
A MULTIPLE – CHANNEL QUEUING MODELS ON FUZZY ENVIRONMENT
A MULTIPLE – CHANNEL QUEUING MODELS ON FUZZY ENVIRONMENTA MULTIPLE – CHANNEL QUEUING MODELS ON FUZZY ENVIRONMENT
A MULTIPLE – CHANNEL QUEUING MODELS ON FUZZY ENVIRONMENTIAEME Publication
 

Plus de IAEME Publication (20)

IAEME_Publication_Call_for_Paper_September_2022.pdf
IAEME_Publication_Call_for_Paper_September_2022.pdfIAEME_Publication_Call_for_Paper_September_2022.pdf
IAEME_Publication_Call_for_Paper_September_2022.pdf
 
MODELING AND ANALYSIS OF SURFACE ROUGHNESS AND WHITE LATER THICKNESS IN WIRE-...
MODELING AND ANALYSIS OF SURFACE ROUGHNESS AND WHITE LATER THICKNESS IN WIRE-...MODELING AND ANALYSIS OF SURFACE ROUGHNESS AND WHITE LATER THICKNESS IN WIRE-...
MODELING AND ANALYSIS OF SURFACE ROUGHNESS AND WHITE LATER THICKNESS IN WIRE-...
 
A STUDY ON THE REASONS FOR TRANSGENDER TO BECOME ENTREPRENEURS
A STUDY ON THE REASONS FOR TRANSGENDER TO BECOME ENTREPRENEURSA STUDY ON THE REASONS FOR TRANSGENDER TO BECOME ENTREPRENEURS
A STUDY ON THE REASONS FOR TRANSGENDER TO BECOME ENTREPRENEURS
 
BROAD UNEXPOSED SKILLS OF TRANSGENDER ENTREPRENEURS
BROAD UNEXPOSED SKILLS OF TRANSGENDER ENTREPRENEURSBROAD UNEXPOSED SKILLS OF TRANSGENDER ENTREPRENEURS
BROAD UNEXPOSED SKILLS OF TRANSGENDER ENTREPRENEURS
 
DETERMINANTS AFFECTING THE USER'S INTENTION TO USE MOBILE BANKING APPLICATIONS
DETERMINANTS AFFECTING THE USER'S INTENTION TO USE MOBILE BANKING APPLICATIONSDETERMINANTS AFFECTING THE USER'S INTENTION TO USE MOBILE BANKING APPLICATIONS
DETERMINANTS AFFECTING THE USER'S INTENTION TO USE MOBILE BANKING APPLICATIONS
 
ANALYSE THE USER PREDILECTION ON GPAY AND PHONEPE FOR DIGITAL TRANSACTIONS
ANALYSE THE USER PREDILECTION ON GPAY AND PHONEPE FOR DIGITAL TRANSACTIONSANALYSE THE USER PREDILECTION ON GPAY AND PHONEPE FOR DIGITAL TRANSACTIONS
ANALYSE THE USER PREDILECTION ON GPAY AND PHONEPE FOR DIGITAL TRANSACTIONS
 
VOICE BASED ATM FOR VISUALLY IMPAIRED USING ARDUINO
VOICE BASED ATM FOR VISUALLY IMPAIRED USING ARDUINOVOICE BASED ATM FOR VISUALLY IMPAIRED USING ARDUINO
VOICE BASED ATM FOR VISUALLY IMPAIRED USING ARDUINO
 
IMPACT OF EMOTIONAL INTELLIGENCE ON HUMAN RESOURCE MANAGEMENT PRACTICES AMONG...
IMPACT OF EMOTIONAL INTELLIGENCE ON HUMAN RESOURCE MANAGEMENT PRACTICES AMONG...IMPACT OF EMOTIONAL INTELLIGENCE ON HUMAN RESOURCE MANAGEMENT PRACTICES AMONG...
IMPACT OF EMOTIONAL INTELLIGENCE ON HUMAN RESOURCE MANAGEMENT PRACTICES AMONG...
 
VISUALISING AGING PARENTS & THEIR CLOSE CARERS LIFE JOURNEY IN AGING ECONOMY
VISUALISING AGING PARENTS & THEIR CLOSE CARERS LIFE JOURNEY IN AGING ECONOMYVISUALISING AGING PARENTS & THEIR CLOSE CARERS LIFE JOURNEY IN AGING ECONOMY
VISUALISING AGING PARENTS & THEIR CLOSE CARERS LIFE JOURNEY IN AGING ECONOMY
 
A STUDY ON THE IMPACT OF ORGANIZATIONAL CULTURE ON THE EFFECTIVENESS OF PERFO...
A STUDY ON THE IMPACT OF ORGANIZATIONAL CULTURE ON THE EFFECTIVENESS OF PERFO...A STUDY ON THE IMPACT OF ORGANIZATIONAL CULTURE ON THE EFFECTIVENESS OF PERFO...
A STUDY ON THE IMPACT OF ORGANIZATIONAL CULTURE ON THE EFFECTIVENESS OF PERFO...
 
GANDHI ON NON-VIOLENT POLICE
GANDHI ON NON-VIOLENT POLICEGANDHI ON NON-VIOLENT POLICE
GANDHI ON NON-VIOLENT POLICE
 
A STUDY ON TALENT MANAGEMENT AND ITS IMPACT ON EMPLOYEE RETENTION IN SELECTED...
A STUDY ON TALENT MANAGEMENT AND ITS IMPACT ON EMPLOYEE RETENTION IN SELECTED...A STUDY ON TALENT MANAGEMENT AND ITS IMPACT ON EMPLOYEE RETENTION IN SELECTED...
A STUDY ON TALENT MANAGEMENT AND ITS IMPACT ON EMPLOYEE RETENTION IN SELECTED...
 
ATTRITION IN THE IT INDUSTRY DURING COVID-19 PANDEMIC: LINKING EMOTIONAL INTE...
ATTRITION IN THE IT INDUSTRY DURING COVID-19 PANDEMIC: LINKING EMOTIONAL INTE...ATTRITION IN THE IT INDUSTRY DURING COVID-19 PANDEMIC: LINKING EMOTIONAL INTE...
ATTRITION IN THE IT INDUSTRY DURING COVID-19 PANDEMIC: LINKING EMOTIONAL INTE...
 
INFLUENCE OF TALENT MANAGEMENT PRACTICES ON ORGANIZATIONAL PERFORMANCE A STUD...
INFLUENCE OF TALENT MANAGEMENT PRACTICES ON ORGANIZATIONAL PERFORMANCE A STUD...INFLUENCE OF TALENT MANAGEMENT PRACTICES ON ORGANIZATIONAL PERFORMANCE A STUD...
INFLUENCE OF TALENT MANAGEMENT PRACTICES ON ORGANIZATIONAL PERFORMANCE A STUD...
 
A STUDY OF VARIOUS TYPES OF LOANS OF SELECTED PUBLIC AND PRIVATE SECTOR BANKS...
A STUDY OF VARIOUS TYPES OF LOANS OF SELECTED PUBLIC AND PRIVATE SECTOR BANKS...A STUDY OF VARIOUS TYPES OF LOANS OF SELECTED PUBLIC AND PRIVATE SECTOR BANKS...
A STUDY OF VARIOUS TYPES OF LOANS OF SELECTED PUBLIC AND PRIVATE SECTOR BANKS...
 
EXPERIMENTAL STUDY OF MECHANICAL AND TRIBOLOGICAL RELATION OF NYLON/BaSO4 POL...
EXPERIMENTAL STUDY OF MECHANICAL AND TRIBOLOGICAL RELATION OF NYLON/BaSO4 POL...EXPERIMENTAL STUDY OF MECHANICAL AND TRIBOLOGICAL RELATION OF NYLON/BaSO4 POL...
EXPERIMENTAL STUDY OF MECHANICAL AND TRIBOLOGICAL RELATION OF NYLON/BaSO4 POL...
 
ROLE OF SOCIAL ENTREPRENEURSHIP IN RURAL DEVELOPMENT OF INDIA - PROBLEMS AND ...
ROLE OF SOCIAL ENTREPRENEURSHIP IN RURAL DEVELOPMENT OF INDIA - PROBLEMS AND ...ROLE OF SOCIAL ENTREPRENEURSHIP IN RURAL DEVELOPMENT OF INDIA - PROBLEMS AND ...
ROLE OF SOCIAL ENTREPRENEURSHIP IN RURAL DEVELOPMENT OF INDIA - PROBLEMS AND ...
 
OPTIMAL RECONFIGURATION OF POWER DISTRIBUTION RADIAL NETWORK USING HYBRID MET...
OPTIMAL RECONFIGURATION OF POWER DISTRIBUTION RADIAL NETWORK USING HYBRID MET...OPTIMAL RECONFIGURATION OF POWER DISTRIBUTION RADIAL NETWORK USING HYBRID MET...
OPTIMAL RECONFIGURATION OF POWER DISTRIBUTION RADIAL NETWORK USING HYBRID MET...
 
APPLICATION OF FRUGAL APPROACH FOR PRODUCTIVITY IMPROVEMENT - A CASE STUDY OF...
APPLICATION OF FRUGAL APPROACH FOR PRODUCTIVITY IMPROVEMENT - A CASE STUDY OF...APPLICATION OF FRUGAL APPROACH FOR PRODUCTIVITY IMPROVEMENT - A CASE STUDY OF...
APPLICATION OF FRUGAL APPROACH FOR PRODUCTIVITY IMPROVEMENT - A CASE STUDY OF...
 
A MULTIPLE – CHANNEL QUEUING MODELS ON FUZZY ENVIRONMENT
A MULTIPLE – CHANNEL QUEUING MODELS ON FUZZY ENVIRONMENTA MULTIPLE – CHANNEL QUEUING MODELS ON FUZZY ENVIRONMENT
A MULTIPLE – CHANNEL QUEUING MODELS ON FUZZY ENVIRONMENT
 

Dernier

Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FMESafe Software
 
Artificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : UncertaintyArtificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : UncertaintyKhushali Kathiriya
 
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...DianaGray10
 
Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...
Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...
Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...Orbitshub
 
Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...
Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...
Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...apidays
 
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdfRising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdfOrbitshub
 
"I see eyes in my soup": How Delivery Hero implemented the safety system for ...
"I see eyes in my soup": How Delivery Hero implemented the safety system for ..."I see eyes in my soup": How Delivery Hero implemented the safety system for ...
"I see eyes in my soup": How Delivery Hero implemented the safety system for ...Zilliz
 
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...apidays
 
DEV meet-up UiPath Document Understanding May 7 2024 Amsterdam
DEV meet-up UiPath Document Understanding May 7 2024 AmsterdamDEV meet-up UiPath Document Understanding May 7 2024 Amsterdam
DEV meet-up UiPath Document Understanding May 7 2024 AmsterdamUiPathCommunity
 
Biography Of Angeliki Cooney | Senior Vice President Life Sciences | Albany, ...
Biography Of Angeliki Cooney | Senior Vice President Life Sciences | Albany, ...Biography Of Angeliki Cooney | Senior Vice President Life Sciences | Albany, ...
Biography Of Angeliki Cooney | Senior Vice President Life Sciences | Albany, ...Angeliki Cooney
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FMESafe Software
 
Why Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire businessWhy Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire businesspanagenda
 
presentation ICT roal in 21st century education
presentation ICT roal in 21st century educationpresentation ICT roal in 21st century education
presentation ICT roal in 21st century educationjfdjdjcjdnsjd
 
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost SavingRepurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost SavingEdi Saputra
 
Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...
Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...
Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...apidays
 
Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Finding Java's Hidden Performance Traps @ DevoxxUK 2024Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Finding Java's Hidden Performance Traps @ DevoxxUK 2024Victor Rentea
 
[BuildWithAI] Introduction to Gemini.pdf
[BuildWithAI] Introduction to Gemini.pdf[BuildWithAI] Introduction to Gemini.pdf
[BuildWithAI] Introduction to Gemini.pdfSandro Moreira
 
TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
TrustArc Webinar - Unlock the Power of AI-Driven Data DiscoveryTrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
TrustArc Webinar - Unlock the Power of AI-Driven Data DiscoveryTrustArc
 
Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...apidays
 

Dernier (20)

Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
 
Artificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : UncertaintyArtificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : Uncertainty
 
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
 
Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...
Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...
Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...
 
Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...
Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...
Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...
 
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdfRising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf
Rising Above_ Dubai Floods and the Fortitude of Dubai International Airport.pdf
 
"I see eyes in my soup": How Delivery Hero implemented the safety system for ...
"I see eyes in my soup": How Delivery Hero implemented the safety system for ..."I see eyes in my soup": How Delivery Hero implemented the safety system for ...
"I see eyes in my soup": How Delivery Hero implemented the safety system for ...
 
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
Apidays New York 2024 - Accelerating FinTech Innovation by Vasa Krishnan, Fin...
 
DEV meet-up UiPath Document Understanding May 7 2024 Amsterdam
DEV meet-up UiPath Document Understanding May 7 2024 AmsterdamDEV meet-up UiPath Document Understanding May 7 2024 Amsterdam
DEV meet-up UiPath Document Understanding May 7 2024 Amsterdam
 
Biography Of Angeliki Cooney | Senior Vice President Life Sciences | Albany, ...
Biography Of Angeliki Cooney | Senior Vice President Life Sciences | Albany, ...Biography Of Angeliki Cooney | Senior Vice President Life Sciences | Albany, ...
Biography Of Angeliki Cooney | Senior Vice President Life Sciences | Albany, ...
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
 
Why Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire businessWhy Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire business
 
presentation ICT roal in 21st century education
presentation ICT roal in 21st century educationpresentation ICT roal in 21st century education
presentation ICT roal in 21st century education
 
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
 
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost SavingRepurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
 
Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...
Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...
Apidays New York 2024 - Passkeys: Developing APIs to enable passwordless auth...
 
Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Finding Java's Hidden Performance Traps @ DevoxxUK 2024Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Finding Java's Hidden Performance Traps @ DevoxxUK 2024
 
[BuildWithAI] Introduction to Gemini.pdf
[BuildWithAI] Introduction to Gemini.pdf[BuildWithAI] Introduction to Gemini.pdf
[BuildWithAI] Introduction to Gemini.pdf
 
TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
TrustArc Webinar - Unlock the Power of AI-Driven Data DiscoveryTrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
 
Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...
 

50120140501013

  • 1. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976INTERNATIONAL JOURNAL OF COMPUTER ENGINEERING & 6367(Print), ISSN 0976 - 6375(Online), Volume 5, Issue 1, January (2014), © IAEME TECHNOLOGY (IJCET) ISSN 0976 – 6367(Print) ISSN 0976 – 6375(Online) Volume 5, Issue 1, January (2014), pp. 112-117 © IAEME: www.iaeme.com/ijcet.asp Journal Impact Factor (2013): 6.1302 (Calculated by GISI) www.jifactor.com IJCET ©IAEME ROBUST CAMPUS WIDE NETWORK DEFENDER Archana D Wankhade1, Dr. P. N. Chatur2 1 2 Assistant Professor in information Technology Department, GCOE, Amravati, India Head and Professor in Computer Science and Engineering Department, GCOE, Amravati, India. ABSTRACT The proposed software architecture is implemented by using agile software development process. The proposed software for the defence against attacks deals with the attack generation, attack detection in the intranet and then prevention of attacks. Attack prevention module is flexible as we can add the rule in the firewall to prevent the any known attack. Due to space problem we considered two attacks on every packet such as ICMP, UDP and TCP packet. Keywords: Smurf, Ping of Death, ICMP Flood, LAND, XMAS, TCP Flood, Ping Pong Attack Generation, Firewall Rules. 1. INTRODUCTION Nations without controlled borders cannot ensure the security and safety of their citizens, nor can they prevent privacy and theft. Similarly, networks without controlled access cannot ensure the security or privacy of stored data, nor can they keep network resources from being exploited by hackers. When internal network is connected to the internet, there is no inherent central point of security control; in fact there is no security at all. Network security is one of the major considerations in computer networking. Various types of tools are being used for providing security to networks. Firewall and Intrusion Detection System are majors among them. We start with description of firewall, types of firewall, comparison between firewalls, followed by algorithms used in our system. Then we will cover IDS part of our system followed by algorithms. Lastly we see programming languages and tools to be used in our system. Security consists of mechanisms for providing confidentiality, integrity, and availability. Confidentiality means that only the individuals allowed access to particular information should be able to access that information. Integrity refers to those controls that prevent information from being altered in any unauthorized manner. Availability controls are those that prevent the proper functioning of computer systems from being interfered 112
  • 2. International Journal of Computer Engineering and Technology (IJCET), ISSN 09766367(Print), ISSN 0976 - 6375(Online), Volume 5, Issue 1, January (2014), © IAEME with. As mentioned in computer network, security of data from network attacks is a major concern area. In most networks firewalls are used as filter to prevent unwanted entry into private network. Firewall is dedicated to only one thing – Deciding between authorized and unauthorized communications. But still firewall cannot detect attacks on network. But IDS has its own limitations. So we try to integrate them in such a way that to get best out of them. 2. LITERATURE SURVEY 2.1 Firewall Firewall is dedicated to only one thing – Deciding between authorized and unauthorized communications. This prevents having to make compromises between security, usability and functionality. Without a firewall, systems are left to their own security devices and configurations. The firewall is a single point of contact between untrusted networks. In general, firewalls mitigate the risk that system will use for unauthorized or unintended purposes. There are three primary attributes that are protected by a firewalls. • Risk to confidentiality • Risk to data integrity • Risk to availability Most common usage of a firewall is between the internet connection and the local area network. Other common firewall usages include protecting connections to external third parties, such as market data providers, and between sensitive areas of an internal network. 2.2 How Firewall Works A firewall is a software program or device that monitors, and sometimes controls, all transmissions between an organization's internal network and the Internet. However large the network, a firewall is typically deployed on the network's edge to prevent inappropriate access to data behind the firewall. The firewall ensures that all communication in both directions conforms to an organization's security policy. Firewall technologies are configurable. You can limit communication by direction, IP address, protocol, ports, or numerous other combinations. If you have access to the firewall, you can configure it to enable the ports, protocols, and addresses. In some cases, however, your organization's security policy may prevent optimal streaming. For example, firewalls configured to only allow TCP traffic may cause the user to see frequent buffering of clips. User experience of the presentation is compromised; greater latency and start up times affect the time needed to view the clip, and delivery of the clip requires more total bandwidth. There are three techniques used for detection • Anomaly detection (behaviour based) • Misuse detection or Signature detection (knowledge based) • State full protocol analysis 113
  • 3. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976 09766367(Print), ISSN 0976 - 6375(Online), Volume 5, Issue 1, January (2014), © IAEME Figure 1.1 Detection Capabilities of Different Intrusion Detection Model Above Figure 1.1 shows detection capabilities of legal and illegal activities, it is misuse for knowledge based and behaviour-based systems. based Anomaly detection: Anomaly detection is describes abnormal patterns behaviour, where “abnormal” patterns it is defined beforehand. Anomaly based models are supposed to describe only legal activities. and Also in this case, incompleteness and inaccuracy can false positive and false negatives. Anomaly-based detection is process of comparing definitions of what activity is based considered normal against observed events to identify significant deviations. An IDPS using ormal anomaly-based detection has profiles that represent the normal behaviour of such things as users, based hosts, network connections, or applications. The profiles are developed by mon monitoring the characteristics of typical activity over a period of time. Following tables are shown comparison of firewalls. Table 1.1 Comparison of firewalls. 114
  • 4. International Journal of Computer Engineering and Technology (IJCET), ISSN 09766367(Print), ISSN 0976 - 6375(Online), Volume 5, Issue 1, January (2014), © IAEME 3. PROPOSED INTRUSION PREVENTION SYSTEM Due to space problems, we have considered very few attacks and their defence mechanisms. The implementation of proposed system is divided into following process: Attack Generation algorithms, Defence Against Attack (Attack Prevention algorithms), Attack Detection Algorithms. Some of the sample attack detection and prevention rules are discussed below: 3.1 Attack Generation algorithms Packet Capture: We o used TCP dump and window dump to capture the incoming flow of information and analysed this traffic by using the proposed IDS. Attack Generation Process can use different tools like NMAP, Nessus, hping3 and Scapy to generate different kinds of trailer made packet to do the attack. For Attack Generation we used the following tools Scapy(http://www.scapy.org),Nmap(http://www.nmap.org),Hping3http://www.hping.org) 3.1.1 Land Attack Generation: #hping3 –a –spoof -flood <src_ip> <dst_ip> where a:spoof source address src_ip : source ip address which is spoofed dst_ip : destination ip address 3.1.2 XMAS Attack Generation: Using the Hping #hping3 –c 1 –V –p 80 –s 5050 –M 0 –UPF 192.16.0.103 Where c: count V: command line switch for addition information about the packet p : port no , s: source port, M: set the sequence 3.1.3 SYN Flood Attack Generation Using the command: hping3 –S –fast –a <src_ip> <dest_ip> where S : SYN packets are generated fast : 10 packets per second a:for spoofing option src_ip : is a Source ip 3.1.4 XMAS Attack Generation Using Scapy #hping3 –c 1 –V –p 80 –s 5050 –M 0 –UPF 192.16.0.103 Where: src :source ip, dst :destination ip flags : FPU-FIN,PUSH,URGENT count : no of packet to generate. 3.2 Attack Detection Algorithms Attack detection task will be carried out through SnortIDSwww.snort.org),SPADE(www.silicondefence.com/Spice_JCS.pdf,www.silicondefense.org) ,NIDES(www.nides.org),HONEYPOT(www.Honeydpot.org),KESENSOR(www.keyfocus.net/kfsen sor),HONEYD(www.Honeyd.org),TRIPWIRE(www.tripwire.org) 3.2.1 ICMP Attacks Detection: If protocol: ICMP and tyop: Request check if state[ipaddress] : active else if state[ipaddress] :active and returncheck if lastpacket.time < 1 [1in 1sec] count[ipaddress]++ else cout[ipaddress] : 0 if count[ipaddress] > 25 [70 in 1sec] reset count[ipaddress]:0 and lastpacket.time :0 set alarm flag. 3.2.2 Smurf attack Detection: Alert icmp $External_net any : $home_net any (msg:”icmp smurf attack detected”; dsize:4; icmp_id:0 ;icmp_seq:0 ; itype:8 ; classtype: attempted – recon ; sid:78787878; ) 115
  • 5. International Journal of Computer Engineering and Technology (IJCET), ISSN 09766367(Print), ISSN 0976 - 6375(Online), Volume 5, Issue 1, January (2014), © IAEME 3.2.3 SYN Flood Attack Detection: If protocol: TCP and Type: Syn check if state[ipaddress] : active else if state[ipaddress] : active and return check if lastpacket.time < 1 [1in 1sec] count[ipaddress]++ else cout[ipaddress] : 0 if count[ipaddress] > 25 [70 in 1sec] reset count[ipaddress]:0 and lastpacket.time :0 set alarm flag 3.2.4 LAND Attack Detection If protocol: TCP and type: SYN, if Sourceip port == Destination port , if Sourceip ip : Destination ip, set alarm flag Udp Attacks 3.2.5 XMAS Attack Detection: Alert tcp any any : any any (msg: “X mas attack detected” flow: stateless; flags: FPU,12; sid: 1234556;) 3.2.6 Fraggle Attack Detection: alert udp $EXTERNAL_NET any: $HOME_NET any (msg:"UDP_Flood Attack!!!!!"; content:"UDP Flood Test"; flow:stateless; threshold:type threshold, track . 4. CONCLUSIONS Critical literature survey is made in order to carry this work. Enterprise’s general purpose Application firewall / IDS evolved in way that has created conundrum for security. So, prime goal is provide emerging solution which gives hybrid functionality of IDS, IPS, and Firewalls functionality in single box which would be practical and easy to maintain. We have studied various packet generation tools such as Nmap, Nessus, hping3 and Scapy. Then we have made experimentation for the detection of attacks using the open source tools such as snort IDS, NIDES, HONEYPOT KESENSOR, HONEYD, TRIPWIRE, and then we run the various firewalls such as iptable/Netfilter, fwSnort Squid, CCProxy, Kerio. REFERENCES [1] [2] [3] [4] [5] [6] [7] Intrusion detection system using Sax 2.0 and wire shark 1.2.2. Shaw n Conaway, “Using an Intrusion Prevention System as Part of a Layered Security Approach”, Network Support, Technical Enterprises, October-2006. Ido green, tzvi raz, moshe zviran, “analysis of active intrusion prevention data for predicting hostile activity in computer networks”, communications of the acm april 2007/vol. 50, no. 4. suresh n. chari and pau-chen cheng, “BlueBoX: A Policy-Driven, Host-Based Intrusion Detection System”, ACM Transactions on Information and System Security, Vol. 6, No. 2, May 2003. Nong Ye, Senior Member, IEEE, Syed Masum Emran, Qiang Chen, and Sean Vilbert(2002), “Multivariate Statistical Analysis of Audit Trails for Host-Based Intrusion Detection”, ieee transactions on computers, vol. 51, no. 7, july 2002. Fang Yu, T. V. Lakshman, Randy H. Katz (2006), “Efficient Multimatch Packet Classification for Network Security Applications”, ieee journal on selected areas in communications, vol. 24, no. 10, october 2006. Jianchao Han, Mohsen Beheshti, Kazimierz Kowalski, Joel Ortiz, Johnly Tomelden, “Component-based Software Architecture Design for Network Intrusion Detection and Prevention System”, IEEE Computer society Sixth International Conference on Information Technology: New Generations 2009. 116
  • 6. International Journal of Computer Engineering and Technology (IJCET), ISSN 09766367(Print), ISSN 0976 - 6375(Online), Volume 5, Issue 1, January (2014), © IAEME [8] [9] [10] [11] [12] [13] [14] [15] [16] [17] [18] [20] [21] [21] [22] [23] [24] [25] [26] david j., chaboya, richard a. raines, rusty o. aldwin, and barry e. mullins,”Network ntrusion etection Automated and Manual Methods Prone to Attack and Evasion”, published by the ieee computer society, 2006. Jiong Zhang, Mohammad Zulkernine, and Anwar Haque(2008), “Random-Forests-Based Network Intrusion Detection Systems”. Catherine Paquet “Network security using Cisco IDS IPS”, Pearson Education intrusion detection system using Sax 2.0 and wireshark 1.2.2. Nong Ye, Senior Member, IEEE, Syed Masum Emran, Qiang Chen, and Sean Vilbert(2002), “Multivariate Statistical Analysis of Audit Trails for Host-Based Intrusion Detection”, ieee transactions on computers, vol. 51, no. 7, july 2002. George Lawton, “Open Source Security: Opportunity or Oxymoron?” March 2002. K. Salah A. Kahtani(2009), “Improving Snort performance under Linux”, IET Commun., 2009, Vol. 3, Issue. 12. Fang Yu, T. V. Lakshman, Randy H. Katz (2006), “Efficient Multimatch Packet Classification for Network Security Applications”, ieee journal on selected areas in communications, vol. 24, no. 10, october 2006. Jianchao Han, Mohsen Beheshti, Kazimierz Kowalski, Joel Ortiz, Johnly TomeldenComponentbased Software Architecture Design for Network Intrusion Detection and Prevention System, 2009 IEEE Computer society Sixth International Conference on Information Technology: New Generations 2009. Hui Li, Dihua Liu, “Research on Intelligent Intrusion Prevention System Based on Snort”, International Conference on Computer, Mechatronics, Control and Electronic Engineering (CMCE) 2010. Snort Manual and Whitepapers on Rule Optimization, Detection, High-performance multi rule detection engine, Protocol Flow analyzer. All available at the Snort homepage: http://www.sourcefire.com/products/library.html. Jiong Zhang, Mohammad Zulkernine, and Anwar Haque(2008), “Random-Forests-Based Network Intrusion Detection Systems”, vol. 38, no. 5, september 2008. SNORT R Users Manual 2.9.1. Anna Sperotto, Gregor Schaffrath, Ramin Sadre, Cristian Morariu, Aiko Pras and Burkhard Stiller (2010)”An Overview of IP Flow-Based Intrusion Detection”, ieee communications surveys & tutorials, vol. 12, no. 3, third quarter 2010. P.Vigneshwaran and Dr. R. Dhanasekaran, “A Novel Protocol To Improve TCP Performance – Proposal”, International Journal of Computer Engineering & Technology (IJCET), Volume 3, Issue 2, 2012, pp. 372 - 377, ISSN Print: 0976 – 6367, ISSN Online: 0976 – 6375. Kusum Nara and Aman Dureja, “A Dynamic Approach for Improving Performance of Intrusion Detection System Over Manet”, International Journal of Computer Engineering & Technology (IJCET), Volume 4, Issue 4, 2013, pp. 61 - 81, ISSN Print: 0976 – 6367, ISSN Online: 0976 – 6375. Syeda Gauhar Fatima, Dr. Syed Abdul Sattar and Dr.K.Anita Sheela, “Energy Efficient Intrusion Detection System for WSN”, International Journal of Electronics and Communication Engineering & Technology (IJECET), Volume 3, Issue 3, 2012, pp. 246 - 250, ISSN Print: 0976- 6464, ISSN Online: 0976 –6472. JPCAP online tutorial. http://www.cert.org/advisories/CA-1996-01.html. http://www.cert.org/advisories/CA-1996-26.html. 117