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Erschienen in: Peer-to-Peer Networking and Applications 1/2022

11.01.2022

EMBOF-RPL: Improved RPL for early detection and isolation of rank attack in RPL-based internet of things

verfasst von: A. O. Bang, Udai Pratap Rao

Erschienen in: Peer-to-Peer Networking and Applications | Ausgabe 1/2022

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Abstract

Routing Protocol for Low Power and Lossy Networks (RPL) is the only standard protocol that assists the routing process in Low Power and Lossy Networks (LLNs) - based Internet of Things (IoT) applications. However, due to the resource-constrained nature, lack of physical protection and security requirements of the inherent protocol, LLNs are vulnerable to attacks that primarily alter the working of the RPL protocol and disrupt the ongoing communication. Therefore, it is a high profit and desperate target of many attackers. Our work offers a detailed overview of one such significant threat to RPL known as the rank attack. Considering the resource-constrained nature of the IoT devices, we propose and evaluate a lightweight and efficient method to mitigate and isolate the rank attack. Specifically, our approach uses a novel Echelon Metric Based Objective Function (EMBOF) over the default RPL to calculate and check the legitimacy of the advertised rank. The Echelon value is additively determined by the root node and the corresponding parent node(s) in the RPL network topology. Our approach not only detects the attacker node(s) but also isolates it immediately. We implement and evaluate our approach through extensive simulations in Cooja, a Contiki operating system (OS) based simulator. The results of our experiments show the viability of our proposal concerning detection accuracy, isolation latency, packet delivery ratio, end-to-end delay, power consumption and memory overhead.

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Metadaten
Titel
EMBOF-RPL: Improved RPL for early detection and isolation of rank attack in RPL-based internet of things
verfasst von
A. O. Bang
Udai Pratap Rao
Publikationsdatum
11.01.2022
Verlag
Springer US
Erschienen in
Peer-to-Peer Networking and Applications / Ausgabe 1/2022
Print ISSN: 1936-6442
Elektronische ISSN: 1936-6450
DOI
https://doi.org/10.1007/s12083-021-01275-3

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