Title :
An Artificial Immune Model with Danger Theory Based on Changes
Author :
Yin, Mengjia ; Zhang, Tao ; Shu, Yuan
Author_Institution :
Sch. of Comput. & Inf. Sci., Hubei Eng. Univ., Xiaogan, China
Abstract :
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.
Keywords :
artificial immune systems; parameter estimation; AIS efficiency improvement; artificial immune model; biological immunology method; cloud model; danger analysis; danger theory; false positive reduction; system imbalance; systematic parameter estimation; uncertain problems; Computational modeling; Computers; Educational institutions; Entropy; Immune system; Security; Uncertainty; Artificial Immune System; Change; Cloud Model; Danger Signal; Danger Theory;
Conference_Titel :
Computer Science & Service System (CSSS), 2012 International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4673-0721-5
DOI :
10.1109/CSSS.2012.174
