Please use this identifier to cite or link to this item:
https://dspace.ncfu.ru/handle/123456789/32432Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Lapina, M. A. | - |
| dc.contributor.author | Лапина, М. А. | - |
| dc.date.accessioned | 2025-12-12T12:36:15Z | - |
| dc.date.available | 2025-12-12T12:36:15Z | - |
| dc.date.issued | 2026 | - |
| dc.identifier.citation | 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 | ru |
| dc.identifier.uri | https://dspace.ncfu.ru/handle/123456789/32432 | - |
| dc.description.abstract | 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. | ru |
| dc.language.iso | en | ru |
| dc.publisher | Springer Science and Business Media Deutschland GmbH | ru |
| dc.relation.ispartofseries | Lecture Notes in Networks and Systems | - |
| dc.subject | Artificial intelligence (AI) | ru |
| dc.subject | Intrusion detection system (IDS) | ru |
| dc.subject | One class SVM (OC-SVM) | ru |
| dc.subject | Unknown - intrusion detection system (UK-IDS) | ru |
| dc.title | UK-IDS-Machine Learning Based Intrusion Detection System for Unknown Attack Detection | ru |
| dc.type | Статья | ru |
| vkr.inst | Факультет математики и компьютерных наук имени профессора Н.И. Червякова | ru |
| Appears in Collections: | Статьи, проиндексированные в SCOPUS, WOS | |
Files in This Item:
| File | Size | Format | |
|---|---|---|---|
| scopusresults 3828.pdf Restricted Access | 126.96 kB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.