Application of Clonal Selection Clustering Algorithm for Anomaly Detection in Network Security Management

ABSTRACT

Network security being of practical significance, the importance of network application, the network anomaly detection and the generalization ability are studied as a key link in the network security management. The key technology of network security management is based on: artificial intelligence theory as the research object; the clonal selection method of anomaly detection based on fuzzy clustering algorithm, to solve the anomaly detection of low efficiency; high false alarm rate, proposes the compensation method of evidence combination rule based on the rule of sharing, to solve the problem of the information fusion of evidence combination rule of conflict and defects; and P2P trust management model based on the improved evidence combination rule to solve the P2P system. It is however, difficult to effectively deal with the malicious node attack, besides it can’t effectively deal with the uncertain information and other issues.

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