Review of Intrusion Detection Systems Taxonomy, Techniques, Methods and Future Research Directions

被引：2

作者：

Mikulas, Matus ^{[1
]}

Kotuliak, Ivan ^{[1
]}

机构：

[1] Slovak Univ Technol Bratislava, Fac Informat & Informat Technol, Bratislava, Slovakia

来源：

2024 NEW TRENDS IN SIGNAL PROCESSING, NTSP 2024 | 2024年

关键词：

review; IDS; anomaly; taxonomy; machine learning; future directions; INTELLIGENCE;

D O I：

10.23919/NTSP61680.2024.10726305

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In the field of intrusion detection, research has made enormous progress over the past decade, and there are many articles devoted to this issue. Currently, however, intrusion detection covers a very wide spectrum of new technologies, and mapping this area, current trends and open problems could greatly help researchers find their way and choose the path to take. There are also many different reviews and studies in this domain, which provide different taxonomy and categorization for the same terms what is causing confusion, especially for new researchers in this domain. The article is providing comprehensive overview of different Intrusion Detection System (IDS) methodologies, techniques and taxonomy. Also, the most important principles are described so that the reader, after reading it, clearly understands what IDS is and what its different categories are, how it works. A big emphasis is placed on various open problems for future research.

引用

页码：105 / 112

页数：8

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