Types of intrusion detection systems and technologies for cloud computing networks
سال انتشار: 1400
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 133
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شناسه ملی سند علمی:
ITCT14_028
تاریخ نمایه سازی: 21 اردیبهشت 1401
چکیده مقاله:
As network traffic grows and attacks become more prevalent and complex, we must find creative new ways to enhance intrusion detection systems (IDSes). Recently, researchers have begun to harness both machine learning and cloud computing tech‑ nology to better identify threats and speed up computation times. This paper explores current research at the intersection of these two fields by examining cloud-based network intrusion detection approaches that utilize machine learning algorithms (MLAs). Specifically, we consider clustering and classification MLAs, their applicability to modern intrusion detection, and feature selection algorithms, in order to underline prominent implementations from recent research. We offer a current overview of this growing body of research, highlighting successes, challenges, and future directions for MLA-usage in cloud-based network intrusion detection approaches.
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نویسندگان
Nooshin Rezaian Rad
Master of Information Technology Student, Rezvan Campus Of Imam Reza International University, Mashhad, Iran,