Evidence map›Paper›PMID 35901074›Full record

ArticlePloS one2022

THC-RPL: A lightweight Trust-enabled routing in RPL-based IoT networks against Sybil attack.

Danyal Arshad, Muhammad Asim, Noshina Tariq, Thar Baker, Hissam Tawfik, Dhiya Al-Jumeily Obe

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Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Danyal ArshadDepartment of Computer Science, National University of Computer and Emerging Sciences, Islamabad, Pakistan.
Muhammad AsimDepartment of Computer Science, National University of Computer and Emerging Sciences, Islamabad, Pakistan.
Noshina TariqDepartment of Avionics Engineering, Air University, Islamabad, Pakistan.
Thar BakerDepartment of Computer Science, College of Computing and Informatics, University of Sharjah, Sharjah, UAE.
Hissam TawfikDepartment of Electrical Engineering, College of Engineering, University of Sharjah, Sharjah, UAE.
Dhiya Al-Jumeily ObeSchool of Computer Science and Mathematics, Liverpool John Moores University, Liverpool, United Kingdom.ORCID 0000-0002-9170-0568

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Internet of Things (IoT) and its relevant advances have attracted significant scholarly, governmental, and industrial attention in recent years. Since the IoT specifications are quite different from what the Internet can deliver today, many groundbreaking techniques, such as Mobile Ad hoc Networks (MANETs) and Wireless Sensor Networks (WSN), have gradually been integrated into IoT. The Routing Protocol for Low power and Lossy network (RPL) is the de-facto IoT routing protocol in such networks. Unfortunately, it is susceptible to numerous internal attacks. Many techniques, such as cryptography, Intrusion Detection System (IDS), and authorization have been used to counter this. The large computational overhead of these techniques limits their direct application to IoT nodes, especially due to their low power and lossy nature. Therefore, this paper proposes a Trust-based Hybrid Cooperative RPL protocol (THC-RPL) to detect malicious Sybil nodes in an RPL-based IoT network. The proposed technique is compared and evaluated with state-of-the-art and is found to outperform them. It detects more attacks while maintaining the packet loss ratio in the range of 15-25%. The average energy consumption of the nodes also remains in the ratio of 60-80 mj. There is approximately 40% more energy conservation at node level with an overall 50% increase in network lifetime. THC-RPL has 10% less message exchange and 0% storage costs.

Indexed as

Computer Communication NetworksInternet of ThingsAlgorithmsTrustWireless Technology

Identifiers

PMID35901074
PMCPMC9333330

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.