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Using Genetic Algorithm to Improve Bernoulli Naïve Bayes Algorithm in Order to Detect DDoS Attacks in Cloud Computing Platform

Journal Name:

  • International Journal of Science and Engineering Investigations

Publication Year:

  • 2018

Key Words:

Author NameUniversity of Author
Abstract (2. Language): 
Devices such as routers, switches or firewalls are the most vital connections in communication network among physical machines in a cloud computing environment. In the absence of security on the network, intruders are allowed to access the equipment and configure it in the way they want to. Hence, a method suggested to deal with denial-of-service (DoS) attacks in the cloud computing platform is one of the essential and most important security issues in this area. This study tends to provide a smart method based on Bernoulli naïve bayes algorithm focusing on genetic algorithm for detecting DoS attacks. Through different network streams, network streams which trigger DoS and DDoS attacks are very important. The main idea of this study is to use Bernoulli naïve bayes algorithm to identify DoS attacks, which is the main reason for optimizing this algorithm using genetic algorithm. In this method, an optimal subset of the set of features is extracted using genetic algorithm, and this optimal subset is used for Bernoulli naïve bayes learning. Results of the experiments carried out and comparison of the suggested method with other methods indicate proper accuracy and operation of the suggested method.
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