Blockchain-Based Decentralized Trust Management in Vehicular Networks

Yang, Zhe; Yang, Kang; Lei, Lei; Zheng, Kan; Leung, Victor C. M.

doi:10.1109/jiot.2018.2836144

Cited by 676 publications

(346 citation statements)

References 22 publications

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“…Figure 26). It is worth noting that in [205] the transactions carrying vehicle reports are essentially unspendable. The RSUs employ weighted average to the rating scores to estimate the quality of the received reports.…”

Section: B Access Control and Self-organizationmentioning

confidence: 99%

A Survey on Consensus Mechanisms and Mining Strategy Management in Blockchain Networks

et al. 2019

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The past decade has witnessed the rapid evolution in blockchain technologies, which has attracted tremendous interests from both the research communities and industries. The blockchain network was originated from the Internet financial sector as a decentralized, immutable ledger system for transactional data ordering. Nowadays, it is envisioned as a powerful backbone/framework for decentralized data processing and datadriven self-organization in flat, open-access networks. In particular, the plausible characteristics of decentralization, immutability and self-organization are primarily owing to the unique decentralized consensus mechanisms introduced by blockchain networks. This survey is motivated by the lack of a comprehensive literature review on the development of decentralized consensus mechanisms in blockchain networks. In this survey, we provide a systematic vision of the organization of blockchain networks. By emphasizing the unique characteristics of incentivized consensus in blockchain networks, our in-depth review of the state-ofthe-art consensus protocols is focused on both the perspective of distributed consensus system design and the perspective of incentive mechanism design. From a game-theoretic point of view, we also provide a thorough review on the strategy adoption for self-organization by the individual nodes in the blockchain backbone networks. Consequently, we provide a comprehensive survey on the emerging applications of the blockchain networks in a wide range of areas. We highlight our special interest in how the consensus mechanisms impact these applications. Finally, we discuss several open issues in the protocol design for blockchain consensus and the related potential research directions.

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Section: B Access Control and Self-organizationmentioning

confidence: 99%

A Survey on Consensus Mechanisms and Mining Strategy Management in Blockchain Networks

et al. 2019

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“…In traditional DPoS consensus schemes, miners are selected from miner candidates according to stake-based voting among stakeholders, i.e., vehicles with stake. In BIoV, as RSUs acting as miner candidates may be distributed along the road without sufficient security protection, they are semi-trusted and may be vulnerable to be directly compromised by attackers [1], [23]. Both stakeholders and miner candidates are vulnerable to arbitrary manipulation by plutocrats [16], and become compromised stakeholders and malicious miner candidates.…”

Section: B Adversary Model For Dpos Consensus Processmentioning

confidence: 99%

Toward Secure Blockchain-Enabled Internet of Vehicles: Optimizing Consensus Management Using Reputation and Contract Theory

Kang

Xiong

Niyato

et al. 2019

IEEE Trans. Veh. Technol.

467

235

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In the Internet of Vehicles (IoV), data sharing among vehicles is critical to improve driving safety and enhance vehicular services. To ensure security and traceability of data sharing, existing studies utilize consensus schemes as hard security solutions to establish blockchain-enabled IoV (BIoV). However, as miners are selected from miner candidates by stake-based voting, defending against voting collusion between the candidates and compromised high-stake vehicles becomes challenging. To address the challenge, in this paper, we propose a two-stage soft security enhancement solution: (i) miner selection and (ii) block verification. In the first stage, we design a reputation-based voting scheme to ensure secure miner selection. This scheme evaluates candidates' reputation using both historical interactions and recommended opinions from other vehicles. The candidates with high reputation are selected to be active miners and standby miners. In the second stage, to prevent internal collusion among active miners, a newly generated block is further verified and audited by standby miners. To incentivize the participation of the standby miners in block verification, we adopt the contract theory to model the interactions between active miners and standby miners, where block verification security and delay are taken into consideration. Numerical results based on a real-world dataset confirm the security and efficiency of our schemes for data sharing in BIoV.Index Terms-Internet of Vehicles, blockchain, reputation management, delegated proof-of-stake, contract theory, security Internet of Vehicles Active minerA malicious active miner RSU RSU Wireless communication Current block manager Standby miner Block verification Miner voting collusion Compromised vehicle Miner voting collusionBlock verification

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“…The unsuccessful transmission probability of data packets ranges from 0% to 40%, and the initial reputation of all the workers is 0.5. We compare the proposed MSL scheme with a Traditional Subjective Logic (TSL) scheme from [7], and an Aggregated Trust Value (ATV) scheme referred to [15]. In the ATV scheme, reputation is calculated by aggregating trust value offsets with different weights from the task publishers.…”

Section: A Simulation Settingmentioning

confidence: 99%

Reliable Federated Learning for Mobile Networks

Kang

Xiong

Niyato

et al. 2020

IEEE Wireless Commun.

394

157

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Federated learning, as a promising machine learning approach, has emerged to leverage a distributed personalized dataset from a number of nodes, e.g., mobile devices, to improve performance while simultaneously providing privacy preservation for mobile users. In the federated learning, training data is widely distributed and maintained on the mobile devices as workers. A central aggregator updates a global model by collecting local updates from mobile devices using their local training data to train the global model in each iteration. However, unreliable data may be uploaded by the mobile devices (i.e., workers), leading to frauds in tasks of federated learning. The workers may perform unreliable updates intentionally, e.g., the data poisoning attack, or unintentionally, e.g., low-quality data caused by energy constraints or high-speed mobility. Therefore, finding out trusted and reliable workers in federated learning tasks becomes critical. In this article, the concept of reputation is introduced as a metric. Based on this metric, a reliable worker selection scheme is proposed for federated learning tasks. Consortium blockchain is leveraged as a decentralized approach for achieving efficient reputation management of the workers without repudiation and tampering. By numerical analysis, the proposed approach is demonstrated to improve the reliability of federated learning tasks in mobile networks.

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Blockchain-Based Decentralized Trust Management in Vehicular Networks

Cited by 676 publications

References 22 publications

A Survey on Consensus Mechanisms and Mining Strategy Management in Blockchain Networks

A Survey on Consensus Mechanisms and Mining Strategy Management in Blockchain Networks

Toward Secure Blockchain-Enabled Internet of Vehicles: Optimizing Consensus Management Using Reputation and Contract Theory

Reliable Federated Learning for Mobile Networks

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