An enhanced steady state genetic algorithm model for misuse network intrusion detection system
Other Title(s)
نموذج محسن للخوارزمية الجينية المستقرة لاكتشاف التطفل في الشبكات الحاسوبية
Dissertant
Thesis advisor
Comitee Members
Salit, Azzam
al-Huraybat, Muhammad
University
Middle East University
Faculty
Faculty of Information Technology
Department
Computer Science Department
University Country
Jordan
Degree
Master
Degree Date
2012
English Abstract
The networks usage has been increased in the last decades.
The intruders began to do violations and abuses over the networks.
This had led the researchers to do additional researches to support Intrusion Detection Systems.
The main aim of this thesis is to build Intrusion Detection System supported by enhanced Steady State Genetic Algorithm in order to increase Detection Rate and to decrease False Positive Rate.
This proposed research proved Reward Penality based Fitness Function to be used in the evaluation process.
It also compared selection and crossover to choose the best choice to implement it in a system; it was found that Stochastic Universal Sampling Selection can be used with Uniform Crossover to produce the best results.
This research was applied Stochastic Universal Sampling Selection and Uniform Crossover as parameters in Steady State Genetic Algorithm to be used in Network Intrusion Detection System.
In this thesis an enhancement has been done to the algorithm by using Reward- Penality based Fitness Function and choosing the best choice for selection and crossover; this has affected the Misuse based Network Intrusion Detection System by increase DR to be equal 95% and decrease FPR to be equal 0.297%.
Main Subjects
Information Technology and Computer Science
No. of Pages
102
Table of Contents
Table of contents.
Abstract.
Abstract in Arabic.
Chapter One : Introduction.
Chapter Two : Theoretical background and literature review.
Chapter Three : Methods and procedures.
Chapter Four : Experimental results.
Chapter Five : Conclusion and future work.
References.
American Psychological Association (APA)
al-Absi, Firas Muhammad Ahmad. (2012). An enhanced steady state genetic algorithm model for misuse network intrusion detection system. (Master's theses Theses and Dissertations Master). Middle East University, Jordan
https://search.emarefa.net/detail/BIM-694120
Modern Language Association (MLA)
al-Absi, Firas Muhammad Ahmad. An enhanced steady state genetic algorithm model for misuse network intrusion detection system. (Master's theses Theses and Dissertations Master). Middle East University. (2012).
https://search.emarefa.net/detail/BIM-694120
American Medical Association (AMA)
al-Absi, Firas Muhammad Ahmad. (2012). An enhanced steady state genetic algorithm model for misuse network intrusion detection system. (Master's theses Theses and Dissertations Master). Middle East University, Jordan
https://search.emarefa.net/detail/BIM-694120
Language
English
Data Type
Arab Theses
Record ID
BIM-694120
