Communications of the ACM
Self-Nonself Discrimination in a Computer
SP '94 Proceedings of the 1994 IEEE Symposium on Security and Privacy
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Bayes Optimality in Linear Discriminant Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
A hybrid intrusion detection system design for computer network security
Computers and Electrical Engineering
A Novel Immunity-Based Anomaly Detection Method
FBIE '08 Proceedings of the 2008 International Seminar on Future BioMedical Information Engineering
A simple and efficient hidden Markov model scheme for host- based anomaly intrusion detection
IEEE Network: The Magazine of Global Internetworking - Special issue title on recent developments in network intrusion detection
AdaBoost-Based Algorithm for Network Intrusion Detection
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Review: An intrusion detection and prevention system in cloud computing: A systematic review
Journal of Network and Computer Applications
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Antibody is one kind of protein that fights against the harmful antigen in human immune system. In modern medical examination, the health status of a human body can be diagnosed by detecting the intrusion intensity of a specific antigen and the concentration indicator of corresponding antibody from human body's serum. In this paper, inspired by the principle of antigen-antibody reactions, we present a New Intrusion Detection Method Based on Antibody Concentration (NIDMBAC) to reduce false alarm rate without affecting detection rate. In our proposed method, the basic definitions of self, nonself, antigen and detector in the intrusion detection domain are given. Then, according to the antigen intrusion intensity, the change of antibody number is recorded from the process of clone proliferation for detectors based on the antigen classified recognition. Finally, building upon the above works, a probabilistic calculation method for the intrusion alarm production, which is based on the correlation between the antigen intrusion intensity and the antibody concentration, is proposed. Our theoretical analysis and experimental results show that our proposed method has a better performance than traditional methods.