Efficient Algorithms for String-Based Negative Selection

Authors:
Michael Elberfeld;Johannes Textor
Affiliations:
Institut für Theoretische Informatik, Universität zu Lübeck, Lübeck, Germany 23538;Institut für Theoretische Informatik, Universität zu Lübeck, Lübeck, Germany 23538
Venue:
ICARIS '09 Proceedings of the 8th International Conference on Artificial Immune Systems
Year:
2009

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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.