Pasikhani, A.M. orcid.org/0000-0003-3181-4026, Clark, J.A. orcid.org/0000-0002-9230-9739, Gope, P. orcid.org/0000-0003-2786-0273 et al. (1 more author) (2021) Intrusion detection systems in RPL-based 6LoWPAN: a systematic literature review. IEEE Sensors Journal, 21 (11). pp. 12940-12968. ISSN 1530-437X
Abstract
Drastic reduction in the manufacturing cost of sensors and actuators has resulted in considerable growth in the number of smart objects. The so-called Internet of Things (IoT) blends the real and virtual environments and removes time and distance barriers. It is widely perceived as a major enabler for the efficient and effective provision of services across a range of sectors. It has naturally attracted the interest of cyberattackers. Due to the heterogeneity, resource-constraints, scale, and internet connectivity of IoT devices, each IoT layer is prone to various threats. Intruders consider the network layer of IoT as the gateway and leverage vulnerabilities in the routing protocol to compromise the Confidentiality, Integrity, and Availability (CIA) of connected nodes. Researchers have proposed different security infrastructures to mitigate harm to IoT networks. One of these is the Intrusion Detection System (IDS). An IDS is an essential component for the network security layer and is widely adopted to reinforce the security of the IoT network. This systematic literature review explores the IPv6 Routing Protocol for Low Power and Lossy Networks (RPL) and its existing threats, classifies relevant IDS techniques and identifies areas requiring further investigation. We review 103 published papers in this domain.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2021 IEEE. |
Keywords: | RPL attacks; IDS taxonomy; detection strategies; 6LoWPAN; monitoring techniques; IoT; LLN |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
Funding Information: | Funder Grant number Engineering and Physical Sciences Research Council EP/S016627/1 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 16 Feb 2024 11:11 |
Last Modified: | 16 Feb 2024 11:11 |
Status: | Published |
Publisher: | Institute of Electrical and Electronics Engineers (IEEE) |
Refereed: | Yes |
Identification Number: | 10.1109/jsen.2021.3068240 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:209247 |