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Заглавие документа: | Sequence Alignment Algorithms for Intrusion Detection in the Internet of Things |
Авторы: | Kalinin, M. Krundyshev, V. |
Тема: | ЭБ БГУ::ЕСТЕСТВЕННЫЕ И ТОЧНЫЕ НАУКИ::Физика |
Дата публикации: | 2020 |
Издатель: | Minsk : Education and Upbringing |
Библиографическое описание источника: | Nonlinear Phenomena in Complex Systems. - 2020. - Vol. 23, N 4. - P. 397-404 |
Аннотация: | The paper reviews the intrusion detection approach based on bioinformatics algorithms for alignment and comparing of the nucleotide sequences. Sequence alignment is a nature-close computational procedure for matching the coded strings by searching for the regions of individual characteristics that are located in the same order. A calculated rank of similarity is used instead of equity checking to estimate the distance between a sequence of the monitored operational acts and a generalized intrusion pattern. Multiple alignment schema is more effective and accurate than the Smith–Waterman local alignment due to ability to find few blocks of similarity. In comparison with a traditional signature-based IDS, it is found that the nature-inspired approach provides the better work characteristics. The experimental study have shown that new approach demonstrates high, 99 percent, level of accuracy. |
URI документа: | https://elib.bsu.by/handle/123456789/274612 |
ISSN: | 1561-4085 |
DOI документа: | 10.33581/1561-4085-2020-23-4-397-404 |
Лицензия: | info:eu-repo/semantics/openAccess |
Располагается в коллекциях: | 2020. Volume 23. Number 4 |
Полный текст документа:
Файл | Описание | Размер | Формат | |
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v23no4p397.pdf | 483,76 kB | Adobe PDF | Открыть |
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