Self-Nonself Recognition Algorithm Based on Positive and Negative Selection(Applications of Information Security Techniques)

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概要

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• In this paper, we propose a self-nonself recognition algorithm based on positive and negative selection used in the developing process of T cells. The anomaly detection algorithm based on negative selection is a representative model among self-recognition method and it has been applied to computer immune systems in recent years. In biological immune systems, T cells are produced through both positive and negative selection. Positive selection is the process used to determine a MHC receptor that recognizes self-molecules. Negative selection is the process used to determine an antigen receptor that recognizes antigens, or nonself cells. In this paper, we propose a self-recognition algorithm based on the positive selection and also propose a fusion algorithm based on both positive and negative selection. To verify the effectiveness of the proposed system, we show simulation results for detecting some infected data obtained from cell changes and string changes in the self-file.

• 社団法人電子情報通信学会の論文
• 2004-02-01

著者

• Sim Kwee-bo

  School Of Electrical And Electronic Engineering Chung-ang University

• Lee Dong-wook

  Information And Telecommunication Research Institute Chung-ang University

関連論文

• Game Theory Based Co-evolutionary Algorithm (GCEA) for Solving Multiobjective Optimization Problems(Artificial Intelligence and Cognitive Science)
• Self-Nonself Recognition Algorithm Based on Positive and Negative Selection(Applications of Information Security Techniques)
• Schema Co-Evolutionary Algorithm (SCEA)(Algorithms)

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