Towards a taxonomy of intrusion-detection systems
Computer Networks: The International Journal of Computer and Telecommunications Networking - Special issue on computer network security
Self-Nonself Discrimination in a Computer
SP '94 Proceedings of the 1994 IEEE Symposium on Security and Privacy
SUTC '06 Proceedings of the IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing -Vol 1 (SUTC'06) - Volume 01
Revisiting Negative Selection Algorithms
Evolutionary Computation
Immune system approaches to intrusion detection --- a review
Natural Computing: an international journal
Theoretical advances in artificial immune systems
Theoretical Computer Science
Immunological Computation: Theory and Applications
Immunological Computation: Theory and Applications
Immune K-means and negative selection algorithms for data analysis
Information Sciences: an International Journal
Information fusion for anomaly detection with the dendritic cell algorithm
Information Fusion
Cellular frustration: a new conceptual framework for understanding cell-mediated immune responses
ICARIS'06 Proceedings of the 5th international conference on Artificial Immune Systems
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
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An negative selection algorithm is presented for intrusion detection tasks for systems with arbitrary diversity. This algorithm uses two types of agents, detectors and presenters. Presenters present information to detectors; detectors are selected to engage in a maximally frustrated dynamics when presenters present data from a reference state. We show that if presenters present information that has never been available during the selection stage, then presenters engage in a less frustrated dynamics and their abnormal presentation can be detected. The performance of our algorithm is independent of the dimension of the space, i.e., the length of information presented by presenters, and hence does not suffer from the dimensionality curse accompanying current methods.