Volume 5, Issue 3, March 2014, Pages 233–240
Parry Gowher Majeed1 and Santosh Kumar2
1 Department of Computer Science and Engineering, Graphic Era University, Dehradun, Uttarakhand, India
2 Department of Computer Science and Engineering, Graphic Era University, Dehradun, Uttarakhand, India
Original language: English
Copyright © 2014 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Securing the digital assets is a major concern in the present digital information era. Various tools and techniques have been researched and implemented to secure the digital assets at both individual and organizational levels. Intrusion detection systems are considered as the cornerstone of modern information security. These systems enable us to be safe from the malicious users, who intend to misuse our digital data and resources. There are different approaches, methods, and techniques employed within the field of intrusion detection. Intrusion detection based on evolutionary methods is currently a hot topic of research. Various evolutionary techniques have been successfully implemented for intrusion detection. In this paper, a survey on applications of genetic algorithms in intrusion detection systems is carried out. The paper provides an introduction to the basic concepts of intrusion detection and genetic algorithms. The generic implementation of genetic algorithms using pseudo code is presented. Pseudo code for genetic algorithm based intrusion detection method is also included for clear understanding. The paper also provides an overview of the advantages and disadvantages of genetic algorithms in general, and as applied to intrusion detection in particular. This survey will provide helpful insight into the related literature and implementation of genetic algorithms in intrusion detection systems. It will also be a good source of information for people interested in the genetic algorithms based intrusion detection systems.
Author Keywords: Misuse Detection, Anomaly Detection, IDS Architecture, Optimization, Classification, Model Generation.
Parry Gowher Majeed1 and Santosh Kumar2
1 Department of Computer Science and Engineering, Graphic Era University, Dehradun, Uttarakhand, India
2 Department of Computer Science and Engineering, Graphic Era University, Dehradun, Uttarakhand, India
Original language: English
Copyright © 2014 ISSR Journals. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
Securing the digital assets is a major concern in the present digital information era. Various tools and techniques have been researched and implemented to secure the digital assets at both individual and organizational levels. Intrusion detection systems are considered as the cornerstone of modern information security. These systems enable us to be safe from the malicious users, who intend to misuse our digital data and resources. There are different approaches, methods, and techniques employed within the field of intrusion detection. Intrusion detection based on evolutionary methods is currently a hot topic of research. Various evolutionary techniques have been successfully implemented for intrusion detection. In this paper, a survey on applications of genetic algorithms in intrusion detection systems is carried out. The paper provides an introduction to the basic concepts of intrusion detection and genetic algorithms. The generic implementation of genetic algorithms using pseudo code is presented. Pseudo code for genetic algorithm based intrusion detection method is also included for clear understanding. The paper also provides an overview of the advantages and disadvantages of genetic algorithms in general, and as applied to intrusion detection in particular. This survey will provide helpful insight into the related literature and implementation of genetic algorithms in intrusion detection systems. It will also be a good source of information for people interested in the genetic algorithms based intrusion detection systems.
Author Keywords: Misuse Detection, Anomaly Detection, IDS Architecture, Optimization, Classification, Model Generation.
How to Cite this Article
Parry Gowher Majeed and Santosh Kumar, “Genetic Algorithms in Intrusion Detection Systems: A Survey,” International Journal of Innovation and Applied Studies, vol. 5, no. 3, pp. 233–240, March 2014.
