Receptor editing-inspired negative selection algorithm

Inspired by theory of biological immune receptor editing, this paper proposes and implements a receptor editing-inspired negative selection algorithm (RENSA). Using directional receptor editing for identifying same nearest selves, the algorithm can simultaneously adjust the position and radius of detectors to expand coverage of non-self space. Theoretical analysis and experimental verification show that the algorithm obtains better detection performance compared with RNS algorithm with fixed detection radius and V-detector algorithm with variable detection radius respectively.