Title Of Paper:
 
 
An Enhanced Solutions for Misuse Network Intrusion Detection System using SGA and SSGA
Author's Name :  Sabah A. Jebur, Hebah H. O. Nasereddin
KeyWords:  Intrusion Detection System, Simple Genetic Algorithm, Steady State Genetic Algorithm
Pages:  14 -23
Volume: 3
Issue: 4
Year: 2015
Abstract:
 

One of the most widely acknowledged purposes of using the internet is data transfer; it is an essential way of communicating personal and sensitive data. Therefore, the need for protecting such data against hackers and intruders is at most importance. Many security systems were built for this purpose; Intrusion Detection Systems (IDS) are one of those systems. The main function of Intrusion Detection System is to monitor the incoming connections and detect attacks. In this paper, the researcher presented two models of IDS. In the first model, the Simple Genetic Algorithm (SGA) was used to build IDS, while in second model; Steady State Genetic Algorithm (SSGA) was used to build IDS. The evaluations and the experiments were performed using the NSL-KDD dataset. The experimental results demonstrated that performing an IDS using SGA gives higher performance results than using SSGA according to the value of Detection rate (DR) and number of new generated rules, also the training time for SGA experiments is shorter than the training time for SSGA. On other hand, SSGA based IDS achieved an average of False Positive Rate (FPR) that was relatively better than SGA based IDS.

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