A new model for dynamic intrusion detection

Tao Li, Xiaojie Liu, Hongbin Li

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

15 Scopus citations

Abstract

Building on the concepts and the formal definitions of self, nonself, antigen, and detector introduced in the research of network intrusion detection, the dynamic evolution models and the corresponding recursive equations of self, antigen, immune-tolerance, lifecycle of mature detectors, and immune memory are presented. Following that, an immune-based model, referred to as AIBM, for dynamic intrusion detection is developed. Simulation results show that the proposed model has several desirable features including self-learning, self-adaption and diversity, thus providing a effective solution for network intrusion detection.

Original languageEnglish
Title of host publicationCryptology and Network Security - 4th International Conference, CANS 2005, Proceedings
Pages72-84
Number of pages13
DOIs
StatePublished - 2005
Event4th International Conference on Cryptology and Network Security, CANS 2005 - Xiamen, China
Duration: 14 Dec 200516 Dec 2005

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3810 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference4th International Conference on Cryptology and Network Security, CANS 2005
Country/TerritoryChina
CityXiamen
Period14/12/0516/12/05

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