DocumentCode
401836
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
Volume
4
fYear
2003
fDate
2-5 Nov. 2003
Firstpage
2437
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);
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2003 International Conference on
Print_ISBN
0-7803-8131-9
Type
conf
DOI
10.1109/ICMLC.2003.1259920
Filename
1259920
Link To Document