TY - GEN
T1 - A new model for dynamic intrusion detection
AU - Li, Tao
AU - Liu, Xiaojie
AU - Li, Hongbin
PY - 2005
Y1 - 2005
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/33744801698
UR - https://www.scopus.com/pages/publications/33744801698#tab=citedBy
U2 - 10.1007/11599371_7
DO - 10.1007/11599371_7
M3 - Conference contribution
SN - 3540308490
SN - 9783540308492
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 72
EP - 84
BT - Cryptology and Network Security - 4th International Conference, CANS 2005, Proceedings
PB - Springer Verlag
T2 - 4th International Conference on Cryptology and Network Security, CANS 2005
Y2 - 14 December 2005 through 16 December 2005
ER -