IEEE Transactions on Software Engineering - Special issue on computer security and privacy
Communications of the ACM
Artificial Immune Systems: A New Computational Intelligence Paradigm
Artificial Immune Systems: A New Computational Intelligence Paradigm
Self-Nonself Discrimination in a Computer
SP '94 Proceedings of the 1994 IEEE Symposium on Security and Privacy
Architecture for an Artificial Immune System
Evolutionary Computation
An artificial immune system architecture for computer securityapplications
IEEE Transactions on Evolutionary Computation
An immunity-based technique to characterize intrusions in computernetworks
IEEE Transactions on Evolutionary Computation
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In the interest of surveying global attacks distributing in the networks, a distributed surveillance model for network security inspired by human immunity is proposed. The proposed model consists of attack detection agent, forensics sub-model, alarm sub-model and risk assessment sub-model. Through simulating immune mechanisms, a detection agent performs selfadaptation and self-learning to generate excellent detection elements and reach the target of attacks recognition. Local agents detect attacks independently and share the learning achievement with the other agents through communication. The sub-models realize the surveying process of evidence extraction, alarms configuration and quantitative risk assessment. Theoretical analysis shows that the proposed model effectively adapts the local network environment and globally improves the surveillance ability of network security.