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Multi-Mobile Agent Trust Framework for Mitigating Internal Attacks and Augmenting RPL Security
Department of Cyber Security, National University of Computer and Emerging Sciences, Islamabad 44000, Pakistan.
Department of Cyber Security, National University of Computer and Emerging Sciences, Islamabad 44000, Pakistan.ORCID iD: 0000-0002-2894-7891
Department of Computer Science, Shaheed Zulfikar Ali Bhutto Institute of Science and Technology, Islamabad 44000, Pakistan.ORCID iD: 0000-0002-9754-253X
Department of Computer Science, College of Computing and Informatics, University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates.ORCID iD: 0000-0002-5166-4873
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2022 (English)In: Sensors, E-ISSN 1424-8220, Vol. 22, no 12, article id 4539Article in journal (Refereed) Published
Abstract [en]

Recently, the Internet of Things (IoT) has emerged as an important way to connect diverse physical devices to the internet. The IoT paves the way for a slew of new cutting-edge applications. Despite the prospective benefits and many security solutions offered in the literature, the security of IoT networks remains a critical concern, considering the massive amount of data generated and transmitted. The resource-constrained, mobile, and heterogeneous nature of the IoT makes it increasingly challenging to preserve security in routing protocols, such as the routing protocol for low-power and lossy networks (RPL). RPL does not offer good protection against routing attacks, such as rank, Sybil, and sinkhole attacks. Therefore, to augment the security of RPL, this article proposes the energy-efficient multi-mobile agent-based trust framework for RPL (MMTM-RPL). The goal of MMTM-RPL is to mitigate internal attacks in IoT-based wireless sensor networks using fog layer capabilities. MMTM-RPL mitigates rank, Sybil, and sinkhole attacks while minimizing energy and message overheads by 25–30% due to the use of mobile agents and dynamic itineraries. MMTM-RPL enhances the security of RPL and improves network lifetime (by 25–30% or more) and the detection rate (by 10% or more) compared to state-of-the-art approaches, namely, DCTM-RPL, RBAM-IoT, RPL-MRC, and DSH-RPL. 

Place, publisher, year, edition, pages
MDPI, 2022. Vol. 22, no 12, article id 4539
Keywords [en]
Internet of Things, RPL, rank attack, Sybil attack, sinkhole attack, trust, mobile agent
National Category
Computer Engineering Signal Processing
Research subject
Information systems
Identifiers
URN: urn:nbn:se:ltu:diva-91967DOI: 10.3390/s22124539ISI: 000817344800001PubMedID: 35746321Scopus ID: 2-s2.0-85132259586OAI: oai:DiVA.org:ltu-91967DiVA, id: diva2:1677980
Note

Validerad;2022;Nivå 2;2022-06-28 (joosat);

Available from: 2022-06-28 Created: 2022-06-28 Last updated: 2022-07-11Bibliographically approved

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Awad, Ali Ismail

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