Title :
Towards an Adaptive Intrusion Detection System: A Critical and Comparative Study
Author :
Bensefia, Hassina ; Ahmed-Nacer, Mohammed
Author_Institution :
Res. Center on the Sci. & Tech. Inf. (CERIST), Algiers, Algeria
Abstract :
An intrusion detection system (IDS) that is destined to supervise an environment, must adjust itself according to every change in the environment and be handling every new attack occurrence. This feature is referred to as the adaptability. It makes the IDS a learning system in relation to its target environment, practicing an autonomous and continuous learning of new attacks. This paper develops a critical and comparative study of existing adaptive intrusion detection models. The objective of such study is to be oriented with regard to related works in the aim of building our own vision to add contribution in the IDS adaptability context.
Keywords :
learning (artificial intelligence); security of data; adaptive intrusion detection system; autonomous learning; continuous learning; learning system; Adaptive systems; Computational intelligence; Computer science; Computer security; Decision making; Information security; Intrusion detection; Learning systems; Monitoring; Telecommunication traffic; Intrusion detection; adaptability; autonomous learning; incremental learning; new attack patterns;
Conference_Titel :
Computational Intelligence and Security, 2008. CIS '08. International Conference on
Conference_Location :
Suzhou
Print_ISBN :
978-0-7695-3508-1
DOI :
10.1109/CIS.2008.94
