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  Approach Using Genetic Algorithm for Intrusion Detection System  
  Authors : Abhijeet Karve
  Cite as:

 

Now a days it is very important to maintain a high level security to ensure a safe and trusted communication of information between various organizations. But secured data communication over internet or any other network is always threats of intrusions and misuses. There are different Soft computing approaches have been proposed to detect the attacks. In this paper we proposed the genetic algorithm to generate the rules with the help of network audit data and for selection of rules used fitness function. The generated rules are used to detect or classify the attacks. By using Genetic Algorithm (GA) we can classify the different types of attack. To implement and measure the performance of system we used the DARPA benchmark dataset and obtained reasonable detection rate.

 

Published In : IJCSN Journal Volume 5, Issue 3

Date of Publication : June 2016

Pages : 544-548

Figures :04

Tables : 02

Publication Link : Approach Using Genetic Algorithm for Intrusion Detection System

 

 

 

Abhijeet Karve : Government College of Engineering, Aurangabad, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad, Maharashtra- 431005, India

 

 

 

 

 

 

 

Computer & Network Security, DARPA 98 Dataset, Genetic Algorithm (GA), Intrusion Detection System (IDS.)

IDS is implemented using GA in two steps. In the first step, GA is used to generate classification rules where as in the second step these rules are used for intrusion detection. This reduces the search space and yields more accurate results while using smaller population and lesser number of generations compared to Gong et al.’s approach. This has reduced the time required for the generation of fittest rules. The given system is run for different generations. As the number of generations is increased, more accurate intrusion detection rates are obtained.

 

 

 

 

 

 

 

 

 

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