An adaptive self-tolerant algorithm for hardware immune system

Authors:
Wenjian Luo;Xin Wang;Ying Tan;Yiguo Zhang;Xufa Wang
Affiliations:
Department of Computer Science and Technology, University of Science and Technology of China, Hefei, China;Department of Computer Science and Technology, University of Science and Technology of China, Hefei, China;Department of Computer Science and Technology, University of Science and Technology of China, Hefei, China;Department of Computer Science and Technology, University of Science and Technology of China, Hefei, China;Department of Computer Science and Technology, University of Science and Technology of China, Hefei, China
Venue:
ICES'05 Proceedings of the 6th international conference on Evolvable Systems: from Biology to Hardware
Year:
2005

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Abstract

Hardware immune systems have been studied with some initial achievements in recent years. Hardware immune systems are inspired by biological immune systems and they are expected to have many interesting characteristics, such as self-adaptive, self-learning and fault tolerant abilities. However, as novel intelligent systems, hardware immune systems are faced with many problems. This paper focuses on autoimmunization that is an inevitable problem when designing a complex hardware immune system. After the costimulation mechanism of biological immune system is simply introduced as a metaphor, a novel self-adaptive and self-tolerant algorithm for hardware immune systems is proposed in this paper. Inspired by the co-stimulation mechanism, the algorithm endows hardware immune systems with the capability of self-tolerance by automatically updating detector set and making the self set more complete. It can increase the accuracy of detection and decrease the rate of false positive effectively. Results of simulation experiments demonstrate the validity of this algorithm.