Self-Nonself Recognition Algorithm Based on Positive and Negative Selection

Kwee-Bo SIM; Dong-Wook LEE

Self-Nonself Recognition Algorithm Based on Positive and Negative Selection

Kwee-Bo SIM, Dong-Wook LEE

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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.

Publication: IEICE TRANSACTIONS on Information Vol.E87-D No.2 pp.481-486

Publication Date: 2004/02/01

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Type of Manuscript: LETTER

Category: Applications of Information Security Techniques

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Kwee-Bo SIM, Dong-Wook LEE, "Self-Nonself Recognition Algorithm Based on Positive and Negative Selection" in IEICE TRANSACTIONS on Information, vol. E87-D, no. 2, pp. 481-486, February 2004, doi: .
Abstract: 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.
URL: https://global.ieice.org/en_transactions/information/10.1587/e87-d_2_481/_p

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@ARTICLE{e87-d_2_481,
author={Kwee-Bo SIM, Dong-Wook LEE, },
journal={IEICE TRANSACTIONS on Information},
title={Self-Nonself Recognition Algorithm Based on Positive and Negative Selection},
year={2004},
volume={E87-D},
number={2},
pages={481-486},
abstract={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.},
keywords={},
doi={},
ISSN={},
month={February},}

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TY - JOUR
TI - Self-Nonself Recognition Algorithm Based on Positive and Negative Selection
T2 - IEICE TRANSACTIONS on Information
SP - 481
EP - 486
AU - Kwee-Bo SIM
AU - Dong-Wook LEE
PY - 2004
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E87-D
IS - 2
JA - IEICE TRANSACTIONS on Information
Y1 - February 2004
AB - 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.
ER -