PhD Dissertation. The University of Memphis. Computer Science.
ABSTRACT: Artificial Immune Systems (AIS) is a research area of developing computational methods inspired by biological immune systems. The approach of negative selection algorithms (NSA) is one of the major models of AIS. This dissertation does a comprehensive survey of NSA and highlights the key components that define a negative selection algorithm. It proposed a new negative selection algorithm called V-detector. It has several important features that alleviate some difficulties in negative selection algorithms. (1) Statistical techniques to estimate the detector coverage. (2) Detectors with variable coverage. (3) A boundary-aware algorithm. (4) The main components of V-detector can be customized. (5) One-shot training. Applicability of negative selection algorithms is discussed in details both to understand the reasonable scenarios to use it and its intrinsic limitations.