Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
Constraint satisfaction with coevolution
New ideas in optimization
Self-Nonself Discrimination in a Computer
SP '94 Proceedings of the 1994 IEEE Symposium on Security and Privacy
Snort - Lightweight Intrusion Detection for Networks
LISA '99 Proceedings of the 13th USENIX conference on System administration
How Do We Evaluate Artificial Immune Systems?
Evolutionary Computation
A Machine Learning Evaluation of an Artificial Immune System
Evolutionary Computation
What have gene libraries done for AIS?
ICARIS'05 Proceedings of the 4th international conference on Artificial Immune Systems
A comparative study of real-valued negative selection to statistical anomaly detection techniques
ICARIS'05 Proceedings of the 4th international conference on Artificial Immune Systems
An immunity-based technique to characterize intrusions in computernetworks
IEEE Transactions on Evolutionary Computation
Combatting financial fraud: a coevolutionary anomaly detection approach
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Review: The use of computational intelligence in intrusion detection systems: A review
Applied Soft Computing
Neuro-immune-endocrine (NIE) models for emergency services interoperatibility
EUROCAST'07 Proceedings of the 11th international conference on Computer aided systems theory
Review Article: Recent Advances in Artificial Immune Systems: Models and Applications
Applied Soft Computing
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The paper presents an approach based on principles of immune systems to the anomaly detection problem. Flexibility and efficiency of the anomaly detection system are achieved by building a model of network behavior based on the self-nonself space paradigm. Covering both self and nonself spaces by hyperrectangular structures is proposed. Structures corresponding to self-space are built using a training set from this space. Hyperrectangular detectors covering nonself space are created using niching genetic algorithm. A coevolutionary algorithm is proposed to enhance this process. Results of experiments show a high quality of intrusion detection, which outperform the quality of recently proposed approach based on hypersphere representation of self-space.