A Decentralized Blockchain-Based Trust Management Protocol for the Internet of Things

Kouicem, Djamel Eddine; Imine, Youcef; Bouabdallah, Abdelmadjid; Lakhlef, Hicham

doi:10.1109/tdsc.2020.3003232

Cited by 52 publications

(38 citation statements)

References 24 publications

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“…Similarly, the latter is the average of the secondhand evidence provided by IoT devices. Hence, we argue that the TRM model proposed in [Kouicem et al, 2020] is trivial and lacks novelty. The use of blockchain in their proposed method is minimal and is only limited to storing the evidence.…”

Section: Trust and Blockchainmentioning

confidence: 94%

“…Stack and stake are two different concepts in computer science terminology and the term "proof-of-stack" has been consistently used throughout the paper and hence cannot be a typo. This also points to an underlying problem with the preliminaries and assumptions adopted by [Kouicem et al, 2020] which we explain later in the following paragraphs.…”

Section: Trust and Blockchainmentioning

confidence: 98%

“…The authors in [Kouicem et al, 2020] propose a blockchain-based TRM for IoT. Their proposed TRM calculates the trust scores for service providers in IoT simply using a weighted average of a direct trust score and an indirect trust score while the weight is a design parameter.…”

Section: Trust and Blockchainmentioning

confidence: 99%

“…Similarly, the authors in [Kumar et al, 2020] propose a secure TRM for smart cities by leveraging blockchain and machine learning. The proposed TRM model itself is summation based and hence more trivial than that of [Kouicem et al, 2020]. However, the authors in [Kumar et al, 2020] also propose a machine learning (ML) approach for anomaly detection using an existing tree-based ML model called XGBoost.…”

Section: Trust and Blockchainmentioning

confidence: 99%

“…The authors in [Kumar et al, 2020], similar to the work proposed by the authors in [Kouicem et al, 2020], propose a new blockchain rather than using the existing one although the use of blockchain in their proposed approach is minimal and is limited to data storing. Unlike [Kouicem et al, 2020], the authors in [Kumar et al, 2020] claim that they design an enhanced proof-of-work consensus mechanism rather than proof-of-stake which assumingly is used by [Kouicem et al, 2020]. However, similar to [Kouicem et al, 2020], the authors in [Kumar et al, 2020] do not present the details of their proposed consensus mechanism nor they prove its economical soundness.…”

Section: Trust and Blockchainmentioning

confidence: 99%

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A holistic approach to trust and reputation management in big data

Zeynalvand¹

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This journey would not be possible without the support of my family; Caring parents who raised me well, my dear wife who gave me strength to carry on, and my lovely sister for whom I was a role model. I sincerely want to thank my supervisors, Assoc. Prof. Jie Zhang and Assoc. Prof. Tony T. Luo whose advice and guidance throughout my PhD has brought me where I am.Likewise, many thanks to the other members of my thesis advisory committee, Prof. Dusit Niyato, Assoc. Prof. Bo An, and Dr. Teo SinGee whose valuable comments helped me overcome the challenges along the way.Finally, I want to express my gratitude to all my friends who shared their valuable experience with me and never denied me their support.

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Section: Trust and Blockchainmentioning

confidence: 94%

Section: Trust and Blockchainmentioning

confidence: 98%

Section: Trust and Blockchainmentioning

confidence: 99%

Section: Trust and Blockchainmentioning

confidence: 99%

Section: Trust and Blockchainmentioning

confidence: 99%

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A holistic approach to trust and reputation management in big data

Zeynalvand¹

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Blockchain‐enhanced trust management for mobile edge computing‐enabled intelligent vehicular collaboration in the 6G era

Wang

Zhu

Xiao

et al. 2023

Trans Emerging Tel Tech

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The rapid development and increasing popularity of mobile devices have facilitated the development of computation‐intensive applications and services, but their constrained compute, storage and battery capabilities have also created the requirements for optimized resource provision and service orchestration. Emerging mobile edge computing (MEC) and next‐generation networks (6G) can meet these requirements of mobile devices by migrating complex computing tasks and large volumes of data to edge servers with acceptable latency, thus effectively enhancing the quality of experience (QoE) of mobile users. Intelligent Vehicular Collaboration, as an intelligent mobile application or service in intelligent connected vehicle (ICV) applications, enables precise and effective driving decisions based on a large amount of real‐time traffic information statistics and intelligent analysis of vehicle status to improve the user driving experience and the efficiency of intelligent transportation systems(ITS). However, the openness and dynamics of wireless communications and the high frequency of information interaction of MEC‐enabled intelligent vehicular collaboration services in the 6G era make them highly vulnerable to cyber attacks. How to achieve dynamically trustworthy, secure, and intelligent vehicular collaboration services in the presence of malicious node access and cyber attacks in the 6G MEC‐enabled vehicular network is a significant challenge. In this paper, we propose a novel blockchain‐enabled trust management mechanism to address this challenge. First, we design a spatiotemporal‐correlated message credibility assessment method and a dynamic mutual trust evaluation method to obtain accurate ratings for messages and mobile nodes respectively. Based on the above methods, we propose an improved blockchain‐based intelligent trust management mechanism that enables transparent, tamper‐evident, and trustworthy secure intelligent vehicular collaboration services while maintaining stable and efficient system performance. Simulation results show that our suggested solutions can efficiently evaluate the trust level of ICVs and achieve efficient and secure intelligent vehicular collaboration with acceptable communication and computation overheads.

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