Computational Intelligence: An Introduction
Computational Intelligence: An Introduction
The utilization of artificial intelligence in a hybrid intrusion detection system
SAICSIT '02 Proceedings of the 2002 annual research conference of the South African institute of computer scientists and information technologists on Enablement through technology
Is negative selection appropriate for anomaly detection?
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Applying both positive and negative selection to supervised learning for anomaly detection
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
A Software Implementation of a Genetic Algorithm Based Approach to Network Intrusion Detection
SNPD-SAWN '05 Proceedings of the Sixth International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing and First ACIS International Workshop on Self-Assembling Wireless Networks
Genetic Programming Based WiFi Data Link Layer Attack Detection
CNSR '06 Proceedings of the 4th Annual Communication Networks and Services Research Conference
A retrovirus inspired algorithm for virus detection & optimization
Proceedings of the 8th annual conference on Genetic and evolutionary computation
On evolving buffer overflow attacks using genetic programming
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Genertia: a system for vulnerability analysis, design and redesign of immunity-based anomaly detection system
An artificial immune system architecture for computer securityapplications
IEEE Transactions on Evolutionary Computation
An immunity-based technique to characterize intrusions in computernetworks
IEEE Transactions on Evolutionary Computation
A formal framework for positive and negative detection schemes
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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As library-based techniques of virus and intrusion detection prove insufficient to be means of protection for computer systems and networks, alternate methods must be incorporated into computer defense. This paper surveys a variety of Artificial Intelligence methods aimed at improving the effectiveness of modern computer security in the face of more prevalent, sophisticated, and ever-changing threats. Specifically, Artificial Immune Systems, Genetic Algorithms, Genetic Programming, and Neural Networks are discussed primarily within the auspices of threat analysis and system testing. Several implemented solutions are discussed and analyzed. Additionally, the paper provides suggestions for the synthesis of varying methods with traditional security in order to create a stronger, more robust security system.