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https://dspace.ncfu.ru/handle/123456789/32432| Название: | UK-IDS-Machine Learning Based Intrusion Detection System for Unknown Attack Detection |
| Авторы: | Lapina, M. A. Лапина, М. А. |
| Ключевые слова: | Artificial intelligence (AI);Intrusion detection system (IDS);One class SVM (OC-SVM);Unknown - intrusion detection system (UK-IDS) |
| Дата публикации: | 2026 |
| Издатель: | Springer Science and Business Media Deutschland GmbH |
| Библиографическое описание: | Sowmya, T., Mary Anita, E. A., Lapina, M. UK-IDS-Machine Learning Based Intrusion Detection System for Unknown Attack Detection // Lecture Notes in Networks and Systems. - 2026. - 1456 LNNS. - pp. 425 - 433. - DOI: 10.1007/978-3-032-07275-7_38 |
| Источник: | Lecture Notes in Networks and Systems |
| Краткий осмотр (реферат): | Computer networks have become the major focus for attackers. Hence intrusion detection system plays a significant role in detecting attacks. Many researchers have already focused on the domain of cyber security by developing an efficient framework. However, developing an efficient IDS is still a challenging task because of its effectiveness in determining novel attacks. Hence in the current study, a machine learning based IDS called UK-IDS is proposed by incorporating OC-SVM and a basic SVM model. The aim of the proposed system is to achieve high accuracy and F1 score by detecting novel attacks. The OC-SVM approach identifies the novel attacks by collaborating the clustering and thresholding mechanism. The basic SVM model is to distinguish the type of attack. The experimental study reveals that UK-IDS framework shows good performance in terms of accuracy and F1 score. |
| URI (Унифицированный идентификатор ресурса): | https://dspace.ncfu.ru/handle/123456789/32432 |
| Располагается в коллекциях: | Статьи, проиндексированные в SCOPUS, WOS |
Файлы этого ресурса:
| Файл | Размер | Формат | |
|---|---|---|---|
| scopusresults 3828.pdf Доступ ограничен | 126.96 kB | Adobe PDF | Просмотреть/Открыть |
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