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 S. Then, use these detectors to partition a monitor set M into self and non-self elements. Implementations of this scheme are often impractical because they need exponential time in the size of S to construct D. Here, we consider r-chunk and r-contiguous detectors, two common implementations that suffer from this problem, and show that compressed representations of D are constructible in polynomial time for any given S and r. Since these representations can themselves be used to classify the elements in M, the worst-case running time of r-chunk and r-contiguous detector based negative selection is reduced from exponential to polynomial.

• Type: Conference
• Year: 2009
• Where: ICARIS
• Authors: Michael Elberfeld, Johannes Textor
• Keywords: Artificial Intelligence, ICARIS 2009, Immune-inspired Classification Scheme, R-contiguous Detector, String-based Negative Selection