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Najam, Chovin, Fakhrudeen, Ahmed. (1401). On the performance of intrusion detection systems for the internet of things: State-of-the-Art in Research. هنرهای کاربردی, 14(1), 1413-1436. doi: 10.22075/ijnaa.2022.7095
Chovin Usman Najam; Ahmed M. Fakhrudeen. "On the performance of intrusion detection systems for the internet of things: State-of-the-Art in Research". هنرهای کاربردی, 14, 1, 1401, 1413-1436. doi: 10.22075/ijnaa.2022.7095
Najam, Chovin, Fakhrudeen, Ahmed. (1401). 'On the performance of intrusion detection systems for the internet of things: State-of-the-Art in Research', هنرهای کاربردی, 14(1), pp. 1413-1436. doi: 10.22075/ijnaa.2022.7095
Najam, Chovin, Fakhrudeen, Ahmed. On the performance of intrusion detection systems for the internet of things: State-of-the-Art in Research. هنرهای کاربردی, 1401; 14(1): 1413-1436. doi: 10.22075/ijnaa.2022.7095

On the performance of intrusion detection systems for the internet of things: State-of-the-Art in Research

International Journal of Nonlinear Analysis and Applications
مقاله 109، دوره 14، شماره 1، فروردین 2023، صفحه 1413-1436    اصل مقاله (772.77 K)
نوع مقاله: Research Paper
شناسه دیجیتال (DOI): 10.22075/ijnaa.2022.7095
نویسندگان
Chovin Usman Najam* 1؛ Ahmed M. Fakhrudeen2
1Computer Science Department, College of Computer Science and Information Technology, Kirkuk University, Kirkuk, Iraq
2Software Department, College of Computer Science and Information Technology, Kirkuk University, Kirkuk, Iraq
تاریخ دریافت: 26 تیر 1401،  تاریخ بازنگری: 02 مهر 1401،  تاریخ پذیرش: 24 مهر 1401 
چکیده
Nowadays, the IoT attracts a multitude of research and industrial interests. Smaller and smarter devices are being implemented daily in multiple IoT domains. However, protecting IoT devices from cyber-attacks is critical to their operation. Confidential data is leaked as a result of malicious acts. As a result, device performance becomes crucial. Security risks are frequently made in IoT-based structures that impact their standard work. Therefore, to eliminate and mitigate these issues (attacks), the Intrusion Detection System (IDS) was proposed to fulfill this purpose. This paper aims to study the state of the art of the proposed IDS. Moving on, we critically review the proposed IDS-based machine learning algorithms. Based on this evaluation criteria, the solutions covering architectures, intelligent prediction and algorithms are critically reviewed. To achieve our goals, the paper presents challenges and open research areas in IoT design.
کلیدواژه‌ها
Internet of Things؛ IoT Security Challenges؛ Intrusion Detection System؛ Machine Learning based IDS
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