The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
A Critical Review of Practices and Challenges in Intrusion Detection Systems for IoT: Toward Universal and Resilient Systems
Abstract
The Internet-of-Things (IoT) is rapidly becoming ubiquitous. However the heterogeneous nature of devices and protocols in use, the sensitivity of the data contained within, as well as the legal and privacy issues, make security for the IoT a growing research priority and industry concern. With many security practices being unsuitable due to their resource intensive nature, it is deemed important to include second line defences into IoT networks. These systems will also need to be assessed for their efficacy in a variety of different network types and protocols. To shed light on these issues, this paper is concerned with advancements in intrusion detection practices in IoT. It provides a comprehensive review of current intrusion detection systems (IDSs) for IoT technologies, focusing on architecture types. A proposal for future directions in IoT based IDS are then presented and evaluated. We show how traditional practices are unsuitable due to their inherent features providing poor coverage of the IoT domain. In order to develop a secure, robust and optimized solution for these networks, the current research for intrusion detection in IoT will need to move in a different direction. An example of which is proposed in order to illustrate how malicious nodes might be passively detected.
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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
A Survey of Data Mining and Machine Learning Methods for Cyber Security Intrusion Detection
Buczak, A. L., & Guven, E. (2016) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2015.2494502 · Cited by 3,332
Low-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
Network Intrusion Detection for IoT Security Based on Learning Techniques
Chaabouni, N., Mosbah, M., Zemmari, A., Sauvignac, C., & Faruki, P. (2019) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2019.2896380 · Cited by 940
Khraisat, A., & Alazab, A. (2021) · Cybersecurity · doi:10.1186/s42400-021-00077-7 · Cited by 508
Machine learning based solutions for security of Internet of Things (IoT): A survey
Tahsien, S. M., Karimipour, H., & Spachos, P. (2020) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2020.102630 · Cited by 470
Shafiq, M., Tian, Z., Sun, Y., Du, X., & Guizani, M. (2020) · Future Generation Computer Systems · doi:10.1016/j.future.2020.02.017 · Cited by 384
Asharf, J., Moustafa, N., Khurshid, H., Debie, E., Haider, W., & Wahab, A. (2020) · Electronics · doi:10.3390/electronics9071177 · Cited by 378
Metadata
- Authors
- Benkhelifa, E., Welsh, T., & Hamouda, W.
- Venue
- IEEE Communications Surveys & Tutorials
- Published
- 2018
- Volume
- 20
- Issue
- 4
- Pages
- 3496-3509
- ISSN
- 1553-877X (ISSN-L)
- 2373-745X
- OpenAlex
- W2806697149
- Cited by
- 233
- References
- 3
- FWCI
- 14.94
- Type
- journal article
- Language
- en
- Open access
- closed
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- Benkhelifa, E., Welsh, T., & Hamouda, W. (2018). A Critical Review of Practices and Challenges in Intrusion Detection Systems for IoT: Toward Universal and Resilient Systems. IEEE Communications Surveys & Tutorials. https://doi.org/10.1109/comst.2018.2844742
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