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» An evolutionary algorithm to generate hyper-ellipsoid detect...
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GECCO
2005
Springer
121views Optimization» more  GECCO 2005»
13 years 10 months ago
An evolutionary algorithm to generate hyper-ellipsoid detectors for negative selection
This paper introduces hyper-ellipsoids as an improvement to hyper-spheres as intrusion detectors in a negative selection problem within an artificial immune system. Since hyper-s...
Joseph M. Shapiro, Gary B. Lamont, Gilbert L. Pete...
GECCO
2005
Springer
113views Optimization» more  GECCO 2005»
13 years 10 months ago
Estimating the detector coverage in a negative selection algorithm
This paper proposes a statistical mechanism to analyze the detector coverage in a negative selection algorithm, namely a quantitative measurement of a detector set’s capability ...
Zhou Ji, Dipankar Dasgupta
IAW
2003
IEEE
13 years 10 months ago
An Evolutionary Approach to Generate Fuzzy Anomaly Signatures
Abstract— This paper describes the generation of fuzzy signatures to detect some cyber attacks. This approach is an enhancement to our previous work, which was based on the princ...
Fabio A. González, Jonatan Gómez, Ma...
GECCO
2010
Springer
155views Optimization» more  GECCO 2010»
13 years 9 months ago
Negative selection algorithms without generating detectors
Negative selection algorithms are immune-inspired classifiers that are trained on negative examples only. Classification is performed by generating detectors that match none of ...
Maciej Liskiewicz, Johannes Textor
ICARIS
2009
Springer
13 years 8 months ago
Efficient Algorithms for String-Based Negative Selection
Abstract. String-based negative selection is an immune-inspired classification scheme: Given a self-set S of strings, generate a set D of detectors that do not match any element of...
Michael Elberfeld, Johannes Textor