PCC-RPL: An efficient trust-based security extension for RPL

Pishdar, Mohammad; Seifi, Younes; Nasiri, Mohammad; Bag-Mohammadi, Mozafar

doi:10.1080/19393555.2021.1887413

Cited by 8 publications

(4 citation statements)

References 19 publications

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“…Any malicious activity detected by a parent reduces the trust level associated with the child and alerts the root node by transmitting a suspicious message. The article [16] addresses the security of IoT networks by exploiting vulnerabilities in the message queuing telemetry transport (MQTT) protocol. To discover new security vulnerabilities in MQTT, a fuzzy attack approach was proposed to detect security breaches.…”

Section: Vulnerability Analysis In Rpl-based Approachesmentioning

confidence: 99%

Federated Learning-based Routing Vulnerability Analysis and Attack Detection for Healthcare 4.0

2024

IJIES

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Industrial 4.0 technological breakthroughs highly impact healthcare 4.0 and enable transformative impact on the healthcare system by shifting towards efficient, patient-centric, data-driven, and robust global healthcare services. This paper presents a robust security framework; federated learning (FL) based RPL vulnerability analysis and attack detection (FRVA), for ensuring secure Healthcare 4.0. The FRVA is proposed to defend the RPLhealthcare 4.0 against multiple attacks by applying deep learning-based fuzzing and FL-enabled hybrid learning. RPL vulnerabilities are analyzed using randomly generated inputs by deep learning-based fuzzing. Further, it feeds the RPL vulnerability-rich fuzzed output dataset to the FL-hybrid learning model. The second model improved the customized local learning models using globally shared information according to FL, resulting in high learning accuracy with precise attack detection. The proposed FRVA runs the vulnerability analysis and attack detection at the edges to prolong the network lifetime with high security. Moreover, the performance of the FRVA is validated through Python-based simulations using different metrics. The simulation results demonstrate that the proposed FLbased hybrid CNN-LSTM strategy enhances the accuracy by 5.55% and 12.9%, respectively, compared with the individual CNN and LSTM methods. It also enhances the accuracy by 25.83% and 5.97% than the other conventional FL-based detection strategies.

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Section: Vulnerability Analysis In Rpl-based Approachesmentioning

confidence: 99%

Federated Learning-based Routing Vulnerability Analysis and Attack Detection for Healthcare 4.0

2024

IJIES

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“…For most IoT deployments, some measure of security is required based on factors such as the type of application, the location of deployment, and the significance of the data being provided [95]- [97]. IoT apps benefit from having trust, authenticity, authentication, availability, privacy, and integrity.…”

Section: Securitymentioning

confidence: 99%

Review of routing protocol for low power and lossy network in the internet of things

Saare,

Lashari,

Khalil

et al. 2023

IJEECS

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The growth of internet of things (IoT) devices and apps has caused disruptions in key sectors such as smart environment, healthcare, and mission-critical tool. Security of IoT devices, networks, and infrastructure is the biggest challenge. RPL, a routing protocol optimised for low-power and lossy networks, is applied by the IoT to offer seamless information transfer among the myriad of interconnected entities. So, the paper delves into the nuts and bolts of RPL, covering its protocol settings, trickle timer, and objective function, as well as the IoT’s architecture and applications. This article also provides a framework for categorising past research on the effects of RPL-IoT on energy consumption, transportation, service quality, traffic congestion, and safety. The future of energy efficiency, congestion, objective function, mobility, stability, security, collaborative intrusion detection systems, active learning, and Key Management are all considered in this analysis.

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“…In one study, a new approach called the PCC-RPL (Parental Change Control RPL) was introduced to manage changes made by parents to IoT devices using the trust concept. This model's calculations are carried out at the node level of the topology [15]. In another study, a model was developed for enhancing RPL security and mitigating vulnerabilities to WSN-inherited and RPL-specific attacks.…”

Section: Related Workmentioning

confidence: 99%

A Subjective Logical Framework-Based Trust Model for Wormhole Attack Detection and Mitigation in Low-Power and Lossy (RPL) IoT-Networks

Javed,

Sajid,

Kiren

et al. 2023

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The increasing use of wireless communication and IoT devices has raised concerns about security, particularly with regard to attacks on the Routing Protocol for Low-Power and Lossy Networks (RPL), such as the wormhole attack. In this study, the authors have used the trust concept called PCC-RPL (Parental Change Control RPL) over communicating nodes on IoT networks which prevents unsolicited parent changes by utilizing the trust concept. The aim of this study is to make the RPL protocol more secure by using a Subjective Logic Framework-based trust model to detect and mitigate a wormhole attack. The study evaluates the trust-based designed framework known as SLF-RPL (Subjective Logical Framework-Routing Protocol for Low-Power and Lossy Networks) over various key parameters, i.e., low energy consumption, packet loss ratio and attack detection rate. The achieved results were conducted using a Contiki OS-based Cooja Network simulator with 30, 60, and 90 nodes with respect to a 1:10 malicious node ratio and compared with the existing PCC-RPL protocol. The results show that the proposed SLF-RPL framework demonstrates higher efficiency (0.0504 J to 0.0728 J out of 1 J) than PCC-RPL (0.065 J to 0.0963 J out of 1 J) in terms of energy consumption at the node level, a decreased packet loss ratio of 16% at the node level, and an increased attack detection rate at network level from 0.42 to 0.55 in comparison with PCC-RPL.

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PCC-RPL: An efficient trust-based security extension for RPL

Cited by 8 publications

References 19 publications

Federated Learning-based Routing Vulnerability Analysis and Attack Detection for Healthcare 4.0

Federated Learning-based Routing Vulnerability Analysis and Attack Detection for Healthcare 4.0

Review of routing protocol for low power and lossy network in the internet of things

A Subjective Logical Framework-Based Trust Model for Wormhole Attack Detection and Mitigation in Low-Power and Lossy (RPL) IoT-Networks

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