Network fault detection using immune Danger Model
Computation spending is great and false detection rate is high using the traditional immune theory based on SNS(Self-NonSelf) Recognition model in the detection of a network composed of multiple test points. Inspired by danger model theory in biological immunology, in this paper, it is proposed a novel immune faults detection algorithm by combining traditional immune algorithm with danger model theory, and this algorithm is applied to a network composed of multiple test points. In this algorithm, a danger signal is considered to be a fault signal by analysis and comprehensive evaluation. The experimental results proved that the algorithm not only simplifies the calculation process, but also has a higher efficiency and low false detection rate.
SNS(Self-NonSelf) Recognition model immunity theory danger model network fault detection
TIAN Yu-ling Lihui
College of Computer & Software, Taiyuan University of Technology, Taiyuan 030024, China College of Computer & Software, Taiyuan University of Technology, Taiyuan 030024, China College of C
国际会议
The 24th Chinese Control and Decision Conference (第24届中国控制与决策学术年会 2012 CCDC)
太原
英文
1305-1308
2012-05-23（万方平台首次上网日期，不代表论文的发表时间）