Immune-inspired pattern recognition algorithm for anomaly detection

Abstract

The discovery of new functionalities through the study of human physiology has contributed towards the development of artificial immune recognition system. The fundamental idea of this technique is to exploit the innate pattern recognition in immune system. In this paper, we import the concept of PAMPs (Pathogen-Associated Molecular Patterns) in PRRs (Pattern Recognition Receptors) model using the functionality of Dendritic Cell(DQ with Danger Theory. PAMPs are used as one of the signals for detection and the signal value is normalized from the data. We present the derivation of bio-inspired anomaly detection from die DC functionality, and depict an example of how the proposed approach can be applied for computer and network security issues with preliminary results.