Please use this identifier to cite or link to this item: https://ruomo.lib.uom.gr/handle/7000/867
Title: Intrusion Detection Systems for RPL Security: A Comparative Analysis
Authors: Simoglou, George
Violettas, George
Petridou, Sophia
Mamatas, Lefteris
Type: Article
Subjects: FRASCATI::Engineering and technology
FRASCATI::Engineering and technology::Other engineering and technologies
Keywords: IoT
RPL Routing Protocol
Attacks
Intrusion Detection Systems
Issue Date: 8-Feb-2021
Publisher: Elsevier
Source: Computers & Security
First Page: 102219
Abstract: Internet of Things (IoT) is an emerging technology that has seen remarkable blossom over the last years. The growing interest for IPv6 constrained networks has made the Routing Protocol for Low Power and Lossy Networks (RPL) the standard routing solution, which has gained significant attention and maturity in the literature. However, due to the networks' open and possibly unattended environment of operation, as well as to the nodes’ constraints, the security of the protocol is a challenging issue, currently under thorough investigation. New and innovative Intrusion Detection Systems (IDSs) have been proposed in the literature over the last years to address the protocol's security issues. In that regard, our survey paper: i) begins with extracting a set of design requirements for RPL-related IDSs based on discussing the diversity of attacks on the protocol and investigating their impact; ii) continues with identifying best practices and gaps in an IDS design which are derived by studying the evolution of the related bibliography (2013-2020); and iii) concludes with a number of guidelines extracted once we map the 22 IDSs under study to the attacks they encounter and compare them in line with the design requirements we introduce. Our analysis considers feedback from the corresponding authors for a deeper investigation.
URI: https://doi.org/10.1016/j.cose.2021.102219
https://ruomo.lib.uom.gr/handle/7000/867
ISSN: 0167-4048
Electronic ISSN: 0167-4048
Other Identifiers: 10.1016/j.cose.2021.102219
Appears in Collections:Department of Applied Informatics

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