DYNAMIC V-DETECTOR NEGATIVE SELECTION ALGORITHM FOR INTRUSION DETECTION

摘要：

In this study, we introduce a dynamic update strategy of Vdetectors into the negative selection algorithm and apply the improved V-detector negative selection algorithm, called Dynamic V-detector Algorithm (DVA), to network intrusion detection. The dynamic update strategy of Vdetectors makes the algorithm more adaptive and robust for high dimension data especially when the training data is inadequate to cover all the intrusion data. Therefore, DVA can get higher detection rate and lower false alarm rate, and the results are more stable than the original one. Simulation results show that DVA outperforms the original V-detector algorithm in dealing with intrusion detection problems. The results also demonstrate that the dynamic update strategy makes the V-detector Algorithm more effective.

关键词： artificial immune system negative selection algorithm V-detector nNetwork security intrusion detection

作者: Maoguo Gong Licheng Jiao Kang Zhang Jie Yang Lining Zhang

作者单位: Key Lab of Intelligent Perception and Image Understanding of Ministry of Education of China,Institute of Intelligent Information Processing,Xidian University,Xi’an 710071,China

会议类型: 国际会议

会议名称: 2008年拟人系统国际会议(2008 International Conference on Humanized Systems )(ICHS’08)

会议地点: 北京

会议语种:英文

在线出版日期: 2008-10-18（万方平台首次上网日期，不代表论文的发表时间）