DocumentCode
3347826
Title
T-Cell detector maturation algorithm based on cooperative co-evolution GA
Author
Jinyin Chen ; Dongyong Yang ; Zhilin Feng
Author_Institution
Inf. Eng. Coll., Zhejiang Univ. of Technol., Hangzhou, China
Volume
4
fYear
2011
fDate
26-28 July 2011
Firstpage
2295
Lastpage
2299
Abstract
Efficient T-cell detector maturation algorithm is one of the most important problems of anomaly detection. Aiming at solving problems of current algorithms, such as low TP value, fixed matching threshold value and large detector set size. A novel T-detector maturation algorithm based on cooperative co-evolution genetic algorithm is put forward in this paper. According to morphologic analysis of intrusion detection system and covering problem algorithm. And then each population evolves according to each self partition and their best population would be combined as the final matured detector set, which decreases redundancy of detectors and maintains diversity of detectors. The efficiency is proved by theoretical foundation and tests.
Keywords
genetic algorithms; security of data; T-cell detector maturation algorithm; anomaly detection; cooperative co-evolution GA; cooperative co-evolution genetic algorithm; covering problem algorithm; fixed matching threshold value; intrusion detection system; large detector set size; low TP value; morphologic analysis; Algorithm design and analysis; Detectors; Genetic algorithms; Heuristic algorithms; Intrusion detection; Partitioning algorithms; Redundancy; Cooperative co-evolution GA; Detector maturation algorithm; Morphological space; NSA;
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Computation (ICNC), 2011 Seventh International Conference on
Conference_Location
Shanghai
ISSN
2157-9555
Print_ISBN
978-1-4244-9950-2
Type
conf
DOI
10.1109/ICNC.2011.6022387
Filename
6022387
Link To Document