Application of Neural Network Based on Ant Colony Algorithm in Intrusion Detection
Depending on the advantages of self-adaptation, self-learning and self-organization, neural network plays an important role in the field of intrusion detection. But traditional back-propagation algorithm has such shortcomings as slow convergent speed and easy convergence to the local minimum points. Ant colony system is a novel simulated evolutionary algorithm. It has positive feedback, distributed computation, and use of a constructive greedy heuristic. An intrusion detection model that combined ant colony algorithm with neural network was proposed. It not only has the extensive mapping ability of neural network, but also has the advantages of high efficiency, rapid global convergence and distributed computation of ant system. The experimental result indicates good performance can be obtained by neural network based on ant colony algorithm in application of the intrusion detection.
ant colony algorithm neural network intrusion detection back-propagation algorithm
Jiang Zhongyun
Department of Information Shanghai Jianqiao College Shanghai, China
国际会议
成都
英文
490-493
2010-12-17（万方平台首次上网日期，不代表论文的发表时间）