Self-Nonself Discrimination in a Computer
SP '94 Proceedings of the 1994 IEEE Symposium on Security and Privacy
An Immunological Approach to Change Detection: Algorithms, Analysis and Implications
SP '96 Proceedings of the 1996 IEEE Symposium on Security and Privacy
Anomaly Detection Using Real-Valued Negative Selection
Genetic Programming and Evolvable Machines
An evolutionary algorithm to generate hyper-ellipsoid detectors for negative selection
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Application areas of AIS: The past, the present and the future
Applied Soft Computing
A Novel Anomaly Detection Algorithm Based on Real-Valued Negative Selection System
WKDD '08 Proceedings of the First International Workshop on Knowledge Discovery and Data Mining
On the use of hyperspheres in artificial immune systems as antibody recognition regions
ICARIS'06 Proceedings of the 5th international conference on Artificial Immune Systems
Immune-Inspired Adaptable Error Detection for Automated Teller Machines
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
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A new algorithm of detector generation for negative selection algorithm is introduced by adding a big detector to reach a high coverage of non-self space. While the big detector can be variable in different shape using this concept, the paper puts forward an algorithm using a ring-hyper-sphere shaped detector as a big detector. The algorithm is tested using different self set(or training set) and real-word dataset. Preliminary results demonstrate that the new approach enhances the negative selection algorithm in efficiency and reliability without significant increase in complexity.