Major project pdpu

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MAJOR
PROJECT
19BCP029 DHRUMIN PATEL
19BCP041 DWIREPH PARMAR

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Designing a Machine Learning Code to
detect DoS and DDoS attacks in Firewall

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Literature Review
 1. DoS/DDoS attacks are done on Websites
which mostly runs on FIFO/Drop-Tail
algorithms
 2. Almost 65% of web cyber attacks
happens with malicious ware of DoS/DDoS

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Litreature Review
 3. DoS/DDoS attacks are done for gaining
personal benefits or for ransom money by an
Individual or a group of attackers.
 4. Each system has its own methodologies.
A system always contains some weak-points
to host an attack or loop holes which the
attackers use to attack the system

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Prevention
 DDoS/DoS attacks can be prevented using a secure network of
connection and with firewalls made to prevent DoS/DDoS
attacks
 On a private cloud network, these attacks can be prevented by
securing the private network established in the cloud
 The best way to prevent the attacks is to update the fire-walls
and strengthen the system against such kind of attacks from
time-to-time and regular updates

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Progress Report
 Found the dataset on Kaggle
 Did data pre-processing and reduced number of features
 Used algorithms like K-NN and DCT
 Got accuracies and improved them
 Feature selection is done with plasma graph and observations

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Findings
 65% of network attacks are done with DoS/DDoS attacks
 Used for personal gains/money
 Attacks usually occurs when the website is growing popular on
networks/ when some new updates are applied on website.
 Best algorithm to detect the attacks is RF and Naïve bais algorithm
 Without outliers reduction and feature reduction, the accuracies of
models DCT and KNN were around 70-75%
 With data pre-processing and feature selection accuracy is
increased to over 95%

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Future Work and Conclusion
 Applying more data pre processing, reducing the feature
dependency
 Exploration of more models and finding the best one out
 Trying to provide a better solution then used in current systems
 Create a model to predict various DoS/DDoS attacks with a
single algorithm

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Future Work and Conclusion
 Current Best model with highest accuracy is Decision Tree