An Artificial Immune Model with Danger Theory Based on Changes

摘要

Danger Theory is a method of biological immunology. It presents an effective method to reduce false positive and improve the efficiency of AIS. Cloud model is an effective tool to transform qualitative concepts into quantitative expressions for uncertain problems. Change is potential causes of system imbalance, and is the basis and sample for danger analysis. This paper uses the concept of Cloud model to estimate systematic parameters and consequently presents the definition of danger signal. We construct an artificial immune model with danger theory based on changes, 'dangerous' work with 'non self' to stimulate the immune response.