Title :
A Fuzzy Anomaly Detection Algorithm for IPv6
Author :
Yao, Li ; Zhitang, Li ; Shuyu, Liu
Abstract :
To accomplish the anomaly detection based on IPv6, genetic algo-rithm can used as a efficacious rules generation technology. We developed a fuzzy anomaly detection model for IPv6, using fuzzy detection anomaly algorithm with negative selection inspired by biol-ogy and propose a fuzzy anomaly detec-tion rules generation technology for IPv6 using genetic algorithm. Using the CERNET2 backbone traffic, this paper tested the performance of the algorithm. The result shows that the proposed system can detect most of IPv6 attacks.
Keywords :
IP networks; data mining; fuzzy set theory; genetic algorithms; telecommunication traffic; CERNET2 backbone traffic; IPv6 attacks; biology; fuzzy anomaly detection algorithm; genetic algorithm; negative selection algorithm; rules generation technology; fuzzy detection; genetic algorithm; negative selection;
Conference_Titel :
Semantics, Knowledge and Grid, 2006. SKG '06. Second International Conference on
Conference_Location :
Guilin
Print_ISBN :
0-7695-2673-X