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
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;
Conference_Titel :
Natural Computation (ICNC), 2011 Seventh International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-9950-2
DOI :
10.1109/ICNC.2011.6022387