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A Systematic Mapping Study on Intrusion Response Systems
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PRE
AI
DOI：10.1109/ACCESS.2024.3381998.png)
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摘要
En 中文
With the increasing frequency and sophistication of network attacks, network administrators are facing tremendous challenges in making fast and optimum decisions during critical situations. The ability to effectively respond to intrusions requires solving a multi-objective decision-making problem. While several research studies have been conducted to address this issue, the development of a reliable and automated Intrusion Response System (IRS) remains unattainable. This paper provides a Systematic Mapping Study (SMS) for IRS, aiming to investigate the existing studies, their limitations, and future directions in this field. A novel semi-automated research methodology is developed to identify and summarize related works. The innovative approach not only streamlines the process of literature review in the IRS field but also has the potential to be adapted and implemented across a variety of research fields. As a result of this methodology, 287 papers related to the IRS were identified from a pool of 6143 studies extracted by the developed web robot based on initial keywords. This highlights its effectiveness in navigating and extracting valuable insights from the extensive body of literature. Furthermore, this research methodology allows the identification of prominent researchers, journals, conferences, and high-quality papers in the field of study.
Keyword:
Bot (Internet)
Taxonomy
Data mining
Systematics
Surveys
Reviews
Intrusion detection
Decision making
Intrusion detection system
intrusion response system
systematic mapping study
期刊
IF:
3.6
论文数:
9.8W
被引数:
29.4W
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