CTRUST: A Dynamic Trust Model for Collaborative Applications in the Internet of Things

Adewuyi, Anuoluwapo A.; Cheng, Hui; Shi, Qi; Cao, Jiannong; MacDermott, Áine; Wang, Xingwei

doi:10.1109/jiot.2019.2902022

Cited by 83 publications

(64 citation statements)

References 30 publications

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“…An example would be an application that allows the SR to request the assistance of some SPs in the collaborative download of a large file by pooling their bandwidths. Each service class is a self-contained collaboration context to which a suitable IoT trust model, such as CTRUST [25], may be applied in selecting the most trustworthy SPs.…”

Section: Iot Service Composition -Concepts and Techniquesmentioning

confidence: 99%

“…Based on the previous work done in [23]- [29], a list of suitable attributes for an ideal TMS for IoT were enumerated and discussed in our previous work [25]. The list consists of the following 9 properties: 1.…”

Section: Ideal Trust Model For Iot Service Compositionmentioning

confidence: 99%

“…In summary, there is a need for a reliable trust model to guide compositions of IoT services. In a previous work, the authors proposed a trust model, CTRUST, which focused on dynamic trust management for collaborative IoT applications [25]. In CTRUST, the parametrization, weighting, maturity, and decay of trust between nodes are accurately modelled based on suitable functional attributes of the nodes in the collaboration context, and in consideration of the trustor's subjective preferences.…”

Section: Introductionmentioning

confidence: 99%

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SC-TRUST: A Dynamic Model for Trustworthy Service Composition in the Internet of Things

Adewuyi

Cheng

Shi

et al. 2022

IEEE Internet Things J.

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A future Internet of Things (IoT) will feature a service-oriented architecture consisting of lightweight computing platforms offering individual, loosely-coupled microservices. Often, an end-user will request a bespoke service that will require a composition of two or more microservices offered by different service providers. However, the underlying complexities of soft compositions and the increased security risks are inherent in such a massively decentralised and distributed architecture. The use of trust management to secure the IoT is well studied in the literature. However, there are limitations to its use in service compositions in the IoT. Specifically, transparent (agnostic) trust composition and decomposition remain key problems for this area. A novel model for trustworthy service compositions in the IoT, SC-TRUST, is therefore proposed to deal with these challenges. In this study, the trust properties of service compositions and the effect of service workflows on transparent trust composition and decomposition are investigated. Based on the findings, relevant trust evaluation functions are derived to guide the compositions. SC-TRUST was implemented in a suitable application and its performance, in terms of the utility derived and the trust accuracy, convergence and resiliency, was evaluated. The results show that SC-TRUST improves the quality of service compositions and adequately mitigates trust-related attacks, thus increasing both efficiency and security.

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Section: Iot Service Composition -Concepts and Techniquesmentioning

confidence: 99%

Section: Ideal Trust Model For Iot Service Compositionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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SC-TRUST: A Dynamic Model for Trustworthy Service Composition in the Internet of Things

Adewuyi

Cheng

Shi

et al. 2022

IEEE Internet Things J.

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“…The system considers the concepts from social and physiological science for computing the trust between IoT objects and their owners. Anuoluwapo et al [34] proposed a collaborative approach that reliably estimates the trust between objects in the IoT network. However, the privacy aspects are not considered in this work.…”

Section: Trust Management In Social Iotmentioning

confidence: 99%

Decentralized Self-Enforcing Trust Management System for Social Internet of Things

Azad

Bag

Hao

et al. 2020

IEEE Internet Things J.

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“…In previous works, 6,15 the authors propose a distributed trust‐based model for an efficient channel's leasing policy in which a Primary User (PU) willingly leases a portion of its channel access to unlicensed Secondary Users (SUs), and in return, these provide cooperative services by adding intentional jamming to counter eavesdropping and employ cooperative relaying to enhance the quality of communication. Nevertheless, the authors in previous studies 10,12,16,19,20 model the cooperative communication in a spectrum aware environment as a statistical framework and hence propose to employ the cooperative adversarial model for analyzing SSDF's consequences on DSA‐enabled CR‐IIoTs.…”

Section: Literature Reviewmentioning

confidence: 99%

Conjoint belief adaption functionality for statistically secure communication paradigm for CR‐IIoTs

Indra

Dhurandher

Raj

2020

Int J Communication

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SummaryIn an infrastructure‐critical manufacturing industry, continuous monitoring of the assembly lines with internet‐integrated sensors in an unforeseeable, stochastic, and harsh environment becomes indispensable for real‐time fault detection, location, and isolation. State‐of‐the‐art literature suggest that the Cognitive Radio‐based Industrial Internet of Things (CR‐IIoTs), a spectrum aware wireless communication paradigm, is best suited for monitoring as they are proficient in overcoming spectrum scarcity in a 2.4‐GHz industrial, scientific, and medical (ISM) band and guarantee a threshold Quality of Service (QoS) in hostile environs. Nonetheless, CR‐IIoTs and the Cognitive Radio‐based network archetype are susceptible to internal and external security threats at the application layer and vulnerable to Spectrum Sensing Data Falsification (SSDF) at Data Link Layer (DLL). In CR‐IIoTs, cooperative spectrum sensing (CSS) is a competent technique to ameliorate the performance of Primary User (PU) detection and optimizes the idle licensed spectrum bands access management. In this paper, a novel belief adaption framework in conjunction with an optimized secure communication scheme (termed as CBAF) based on the Certificateless‐Public Key Cryptography (CL‐PKC) is proposed for robust CSS in CR‐IIoTs. CBAF proficiently provides full‐Perfect Forward Secrecy, Ephemeral Secret Leakage‐Resilience, Public Key Replacement‐Resilience Malicious but Passive KGC‐Resilience, and Key Escrow Resilience. Simulation analysis pertaining to network performance indices ascertains the efficacy of CBAF, as it outperforms the state‐of‐the‐art in throughput, packet delivery ratio, and communication overhead by 8.5%, 6.7%, and 19.9% respectively. Under internal attacks, CBAF outperforms the best from state‐of‐the‐art by 11.3% in On‐Off attack, 19.7% in Data Tampering attack, 21.1% in SDF attack, and 13.4% in DDoS attack.

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CTRUST: A Dynamic Trust Model for Collaborative Applications in the Internet of Things

Cited by 83 publications

References 30 publications

SC-TRUST: A Dynamic Model for Trustworthy Service Composition in the Internet of Things

SC-TRUST: A Dynamic Model for Trustworthy Service Composition in the Internet of Things

Decentralized Self-Enforcing Trust Management System for Social Internet of Things

Conjoint belief adaption functionality for statistically secure communication paradigm for CR‐IIoTs

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