Title :
Intrusion detection based on artificial immune system with self-similar traffic
Author :
Hua, W. ; Wu, Chan-le
Author_Institution :
Sch. of Comput., Wuhan Univ., China
Abstract :
Recently, the self-similarity theory is a hot spot in correlative researches. And in this paper, we utilize the self-similar traffic to improve the results and performance of the intrusion detection based on artificial immune system. The results of the simulation show that we achieved the high detection probability, the low miss probability, the low false alarm probability and the proper Hurst parameter.
Keywords :
multi-agent systems; probability; safety systems; Hurst parameter; artificial immune system; correlative researches; false alarm probability; high detection probability; intrusion detection; low miss probability; self-similar traffic; self-similarity theory; Artificial immune systems; Biology computing; Computer viruses; IP networks; Immune system; Intrusion detection; Monitoring; Telecommunication traffic; Traffic control; Viruses (medical);
Conference_Titel :
Machine Learning and Cybernetics, 2003 International Conference on
Print_ISBN :
0-7803-8131-9
DOI :
10.1109/ICMLC.2003.1259920
