Modeling of positive selection for the development of a computer immune system and a self-recognition algorithm
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Sim, K.-B. | - |
dc.contributor.author | Lee, D.-W. | - |
dc.date.available | 2019-06-26T01:25:30Z | - |
dc.date.issued | 2003-12 | - |
dc.identifier.issn | 1598-6446 | - |
dc.identifier.issn | 2005-4092 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/26258 | - |
dc.description.abstract | The anomaly-detection algorithm based on negative selection of T cells is representative model among self-recognition methods and it has been applied to computer immune systems in recent years. In 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 antigen, or the nonself cell. In this paper, we propose a novel self-recognition algorithm based on the positive selection of T cells. We indicate the effectiveness of the proposed algorithm by change-detection simulation of some infected data obtained from cell changes and string changes in the self-file. We also compare the self-recognition algorithm based on positive selection with the anomaly-detection algorithm. | - |
dc.format.extent | 6 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | 제어·로봇·시스템학회 | - |
dc.title | Modeling of positive selection for the development of a computer immune system and a self-recognition algorithm | - |
dc.title.alternative | Modeling of Positive Selection for the Development of a Computer Immune System and a Self-Recognition Algorithm | - |
dc.type | Article | - |
dc.identifier.bibliographicCitation | International Journal of Control, Automation and Systems, v.1, no.4, pp 453 - 458 | - |
dc.identifier.kciid | ART001191116 | - |
dc.description.isOpenAccess | N | - |
dc.identifier.scopusid | 2-s2.0-4544222221 | - |
dc.citation.endPage | 458 | - |
dc.citation.number | 4 | - |
dc.citation.startPage | 453 | - |
dc.citation.title | International Journal of Control, Automation and Systems | - |
dc.citation.volume | 1 | - |
dc.type.docType | Article | - |
dc.publisher.location | 대한민국 | - |
dc.subject.keywordAuthor | Immune system | - |
dc.subject.keywordAuthor | MHC set | - |
dc.subject.keywordAuthor | Negative selection | - |
dc.subject.keywordAuthor | Positive selection | - |
dc.subject.keywordAuthor | Self-recognition algorithm | - |
dc.subject.keywordPlus | Bacteria | - |
dc.subject.keywordPlus | Cells | - |
dc.subject.keywordPlus | Computer simulation | - |
dc.subject.keywordPlus | Diseases | - |
dc.subject.keywordPlus | Immunology | - |
dc.subject.keywordPlus | Internet | - |
dc.subject.keywordPlus | Pathology | - |
dc.subject.keywordPlus | Viruses | - |
dc.subject.keywordPlus | Immune system | - |
dc.subject.keywordPlus | MHC set | - |
dc.subject.keywordPlus | Negative selection | - |
dc.subject.keywordPlus | Positve selection | - |
dc.subject.keywordPlus | Self-recognition | - |
dc.subject.keywordPlus | Algorithms | - |
dc.description.journalRegisteredClass | scopus | - |
dc.description.journalRegisteredClass | kciCandi | - |
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