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-spheres are a specialization of hyper-ellipsoids, hyperellipsoids retain the benefits of hyper-spheres. However, hyper-ellipsoids are much more flexible, mostly in that they can be stretched and reoriented. The viability of using hyper-ellipsoids is established using several pedagogical problems. We conjecture that fewer hyper-ellipsoids than hyperspheres are needed to achieve similar coverage of nonself space in a negative selection problem. Experimentation validates this conjecture. In pedagogical benchmark problems, the number of hyper-ellipsoids to achieve good results is significantly ( 50%) smaller than the associated number of hyper-spheres.
As an improvement to hyper-spheres detectors, hyper-ellipsoid detectors are generated by evolutionary algorithm (EA) REF .
An evolutionary algorithm to generate hyper-ellipsoid detectors for negative selection
GECCO '05
Computer Science