Internet of Things Botnet Detection Approaches: Analysis and Recommendations for Future Research | |
Wazzan, M (Wazzan, Majda)[ 1 ]; Algazzawi, D (Algazzawi, Daniyal)[ 2 ]; Bamasaq, O (Bamasaq, Omaima)[ 1 ]; Albeshri, A (Albeshri, Aiiad)[ 1 ]; Cheng, L (Cheng, Li)[ 3 ] | |
刊名 | APPLIED SCIENCES-BASEL |
2021 | |
卷号 | 11期号:12页码:1-46 |
关键词 | Internet of ThingsIoTbotnetdetectionsystematic literature reviewSLR |
ISSN号 | 2076-3417 |
DOI | 10.3390/app11125713 |
英文摘要 | Internet of Things (IoT) is promising technology that brings tremendous benefits if used optimally. At the same time, it has resulted in an increase in cybersecurity risks due to the lack of security for IoT devices. IoT botnets, for instance, have become a critical threat; however, systematic and comprehensive studies analyzing the importance of botnet detection methods are limited in the IoT environment. Thus, this study aimed to identify, assess and provide a thoroughly review of experimental works on the research relevant to the detection of IoT botnets. To accomplish this goal, a systematic literature review (SLR), an effective method, was applied for gathering and critically reviewing research papers. This work employed three research questions on the detection methods used to detect IoT botnets, the botnet phases and the different malicious activity scenarios. The authors analyzed the nominated research and the key methods related to them. The detection methods have been classified based on the techniques used, and the authors investigated the botnet phases during which detection is accomplished. This research procedure was used to create a source of foundational knowledge of IoT botnet detection methods. As a result of this study, the authors analyzed the current research gaps and suggest future research directions. |
WOS记录号 | WOS:000666763300001 |
内容类型 | 期刊论文 |
源URL | [http://ir.xjipc.cas.cn/handle/365002/7847] |
专题 | 新疆理化技术研究所_多语种信息技术研究室 |
作者单位 | 1.Chinese Acad Sci, Xinjiang Tech Inst Phys & Chem, Urumqi 830011, Peoples R China 2.King Abdulaziz Univ, Fac Comp & Informat Technol, Informat Syst Dept, Jeddah 21589, Saudi Arabia 3.King Abdulaziz Univ, Fac Comp & Informat Technol, Comp Sci Dept, Jeddah 21589, Saudi Arabia |
推荐引用方式 GB/T 7714 | Wazzan, M ,Algazzawi, D ,Bamasaq, O ,et al. Internet of Things Botnet Detection Approaches: Analysis and Recommendations for Future Research[J]. APPLIED SCIENCES-BASEL,2021,11(12):1-46. |
APA | Wazzan, M ,Algazzawi, D ,Bamasaq, O ,Albeshri, A ,&Cheng, L .(2021).Internet of Things Botnet Detection Approaches: Analysis and Recommendations for Future Research.APPLIED SCIENCES-BASEL,11(12),1-46. |
MLA | Wazzan, M ,et al."Internet of Things Botnet Detection Approaches: Analysis and Recommendations for Future Research".APPLIED SCIENCES-BASEL 11.12(2021):1-46. |
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