Title :
Collaborative Identification of Danger Signal in Artificial Immune System
Author :
Yin, Mengjia ; Zhang, Tao
Author_Institution :
Sch. of Comput. & Inf. Sci., Hubei Eng. Univ., Xiaogan, China
Abstract :
The producing mechanism for danger signals is the most important in the danger theory used in AIS. To determine whether a system is "dangerous" needs more considerations. This paper uses the cloud model to describe the changes of system continuous parameters. For discontinuous change parameters, we use the changes of each parameter as a separate danger signal. The continuous and discontinuous parameters of danger signals together constitute the overall rule library. we use the method that calculating the triggered rules to determine the "danger" or "security" of system, and realize the collaborative identification of danger signals.
Keywords :
artificial immune systems; security of data; signal processing; AIS; artificial immune system; cloud model; collaborative identification; danger signal; danger theory; discontinuous change parameters; rule library; system continuous parameters; system danger; system security; Collaboration; Computational modeling; Computers; Entropy; Generators; Immune system; Security; Artificial Immune System; Cloud Model; Collaborative Identification; Danger Signal; Danger Theory;
Conference_Titel :
Computational and Information Sciences (ICCIS), 2012 Fourth International Conference on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4673-2406-9
DOI :
10.1109/ICCIS.2012.102