CFP last date
20 June 2024
Reseach Article

Use of Genetic Algorithm in Network Security

by L. M. R. J. Lobo, Suhas B. Chavan
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 53 - Number 8
Year of Publication: 2012
Authors: L. M. R. J. Lobo, Suhas B. Chavan
10.5120/8438-2221

L. M. R. J. Lobo, Suhas B. Chavan . Use of Genetic Algorithm in Network Security. International Journal of Computer Applications. 53, 8 ( September 2012), 1-7. DOI=10.5120/8438-2221

@article{ 10.5120/8438-2221,
author = { L. M. R. J. Lobo, Suhas B. Chavan },
title = { Use of Genetic Algorithm in Network Security },
journal = { International Journal of Computer Applications },
issue_date = { September 2012 },
volume = { 53 },
number = { 8 },
month = { September },
year = { 2012 },
issn = { 0975-8887 },
pages = { 1-7 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume53/number8/8438-2221/ },
doi = { 10.5120/8438-2221 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:53:33.858175+05:30
%A L. M. R. J. Lobo
%A Suhas B. Chavan
%T Use of Genetic Algorithm in Network Security
%J International Journal of Computer Applications
%@ 0975-8887
%V 53
%N 8
%P 1-7
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

After overcoming some drawbacks from an improved genetic feedback algorithm based network security policy framework. A motivation was experienced for the need of a strong network security policy framework. In this paper a strong network model for security function is presented. A gene for a network packet is defined through fitness function and a method to calculate fitness function is explained. The basic attacks encountered can be categorized as buffer overflow, array index out of bound, etc. A stress is given on passive attack, active attack, its types and brute force attack. An analysis on recent attacks and security is provided. Finally the best policy using a comparator is found. The main aim of this paper is threat detection, time optimization, performance increase in terms of accuracy and policy automation. For experimenting real data set from the internet and local network is used. Jpcap, winpcap, Colasoft Capsa 7 open source software are used for implementation. 73% efficiency is achieved because we add 3 networking terms such as payload, checksum, and sequence number. A client server environment is made use of.

References
  1. Atish Mishra, Arun Kumar Jhapate, Prakash Kumar ,"Improved Genetic Feedback Algorithm Based Network Security Policy Framework" in Second International Conference on Future Networks on page 8-10. http://ieeexplore. ieee. org/xpl/freeabs_all. jsp?armunber=5431893
  2. Chen Xiao-su Wu Jin-hua Ni Jun 2007 in Wireless Communications, Networking and Mobile Computing, WiCom 2007. Internatinal Conference on page 2278-2281.
  3. Hang-Fei Wang, Xu-Fa Wang and Jia Xue. "An Improved Interactive Genetic Algorithm Incorporating Relevant Feedback"
  4. Atish Mishra, Arun Kumar Jhapate and Prakash Kumar, 2009 "Designing Rule base for Genetic Feedback Algorithm Based Network Security policy Framework using State Machine" on pp 415-417 at International Conference on Signal Processing Systems.
  5. Hoi Chan; Kwok, T. ; IBM Thomas J. Watson Res. Center, Hawthorne, NY June 2006 "A Policy-Based Management System with Automatic Policy Selection and creation capabilities by using a Singular Value Decomposition Technique" .
  6. Atish Mishra, Prakash Kumar 2009 "Storing Scheme for State Machine Based Rule Base of Genetic Feedback Algorithm Based Network Security Policy Framework Depending on Memory Consumption" at IACSIT vol, 3 Singapore.
  7. Jeffrey O. Kephart and William E. Walsh IBM Thomas J. Watson "An Artificial Intelligence Perspective on Automatic Computing Policies" at Research Center Yorktown Heights, New York 10598.
  8. L. P. Kaelbling, M. L. Littman, A. W. Moore. "Reinforcement Learning: A Survey"
  9. Biing Feng Wang, Chien-Hsin Lin. "Improved Algorithms for Finding Gene Teams and Constructing Gene Team Trees"
  10. R. Yavatkar,D. Pendarakis, R. Guerin, January 2000, RFC 2573, "A Framework for Policy-based Admission Control", http://www. faqs. org/rfcs/rfc2753. html.
  11. B. Abdullah*, I. Abd-alghafar**, Gouda I. Salama** and A. Abd-alhafez , "Performance Evaluation of a Genetic Algorithm Based Approach to Network Intrusion Detection System" in 13th International Conference on AEROSPACE SCIENCES & AVIATION TECHNOLOGY, ASAT- 13, May 26 – 28, 2009. http://www. mtc. edu. eg/ASAT13/pdf/CE14. pdf
  12. Gihan Nagib and Wahied G. Ali, "Network Routing Protocol using Genetic Algorithms" in International Journal of Electrical & Computer Sciences IJECS-IJENS Vol: 10 No: 02 10 March 2010. http://www. ijens. org/104302-8686%20IJECS-IJENS. pdf
  13. Suhas Chavan, L. M. R. J Lobo "Network Security Policy Framework and Analysis" in International Journal of Computer Application special issue on Network Security and Cryptography NSC (1):55-58, December 2011. http://www. ijcaonline. org/specialissues/nsc/number1/4325-spe014t
  14. Mohammad Sazzadul Hoque1, Md. Abdul Mukit2 and Md. Abu Naser Bikas "An implementation of intrusion detection system using genetic algorithm" in International journal of network security & its applications (ijnsa), Vol. 4, No. 2, march 2012 http://www. airccse. org/journal/nsa/0312nsa08. pdf
Index Terms

Computer Science
Information Sciences

Keywords

Genetic algorithm Network security policy framework Fitness function