Abstract
This paper presents a technique inspired by the negative selection mechanism of the immune system that can detect foreign patterns in the complement (nonself) space. In particular, the novel pattern detectors (in the complement space) are evolved using a genetic search, which could differentiate varying degrees of abnormality in network traffic. The paper demonstrates the usefulness of such a technique to detect a wide variety of intrusive activities on networked computers. We also used a positive characterization method based on a nearest-neighbor classification. Experiments are performed using intrusion detection data sets and tested for validation. Some results are reported along with analysis and concluding remarks.
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