The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Intrusion detection systems for IoT-based smart environments: a survey
Open accessAbstract
One of the goals of smart environments is to improve the quality of human life in terms of comfort and efficiency. The Internet of Things (IoT) paradigm has recently evolved into a technology for building smart environments. Security and privacy are considered key issues in any real-world smart environment based on the IoT model. The security vulnerabilities in IoT-based systems create security threats that affect smart environment applications. Thus, there is a crucial need for intrusion detection systems (IDSs) designed for IoT environments to mitigate IoT-related security attacks that exploit some of these security vulnerabilities. Due to the limited computing and storage capabilities of IoT devices and the specific protocols used, conventional IDSs may not be an option for IoT environments. This article presents a comprehensive survey of the latest IDSs designed for the IoT model, with a focus on the corresponding methods, features, and mechanisms. This article also provides deep insight into the IoT architecture, emerging security vulnerabilities, and their relation to the layers of the IoT architecture. This work demonstrates that despite previous studies regarding the design and implementation of IDSs for the IoT paradigm, developing efficient, reliable and robust IDSs for IoT-based smart environments is still a crucial task. Key considerations for the development of such IDSs are introduced as a future outlook at the end of this survey.
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Citations
Cites
Internet of Things: A Survey on Enabling Technologies, Protocols, and Applications
Al-Fuqaha, A., Guizani, M., Mohammadi, M., Aledhari, M., & Ayyash, M. (2015) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2015.2444095 · Cited by 8,630
Interoperability in Internet of Things: Taxonomies and Open Challenges
Noura, M., Atiquzzaman, M., & Gaedke, M. (2019) · Mobile Networks and Applications · doi:10.1007/s11036-018-1089-9 · Cited by 693
Cyber and Physical Security Vulnerability Assessment for IoT-Based Smart Homes
Ali, B., & Awad, A. (2018) · Sensors · doi:10.3390/s18030817 · Cited by 344
Self-citationLow-Energy Security: Limits and Opportunities in the Internet of Things
Trappe, W., Howard, R., & Moore, R. S. (2015) · IEEE Security & Privacy · doi:10.1109/msp.2015.7 · Cited by 246
Cited by
Anomaly-based intrusion detection system for IoT networks through deep learning model
Saba, T., Rehman, A., Sadad, T., Kolivand, H., & Bahaj, S. A. (2022) · Computers and Electrical Engineering · doi:10.1016/j.compeleceng.2022.107810 · Cited by 445
Haque, A. K. M. B., Bhushan, B., & Dhiman, G. (2022) · Expert Systems · doi:10.1111/exsy.12753 · Cited by 271
Moustafa, N., Koroniotis, N., Keshk, M., Zomaya, A. Y., & Tari, Z. (2023) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2023.3280465 · Cited by 266
Pundir, S., Wazid, M., Singh, D. P., Das, A. K., Rodrigues, J. J. P. C., & Park, Y. (2020) · IEEE Access · doi:10.1109/access.2019.2962829 · Cited by 202
Metadata
- Authors
- Elrawy, M. F., Awad, A. I., & Hamed, H. F. A.
- Venue
- Journal of Cloud Computing
- Published
- 2018-12
- Volume
- 7
- Issue
- 1
- ISSN
- 2192-113X (ISSN-L)
- OpenAlex
- W2902106343
- Cited by
- 481
- References
- 4
- FWCI
- 23.65
- Type
- journal article
- Language
- en
- Open access
- gold
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