Blockchain for Secure and Efficient Data Sharing in Vehicular Edge Computing and Networks

By Jiawen Kang, Rong Yu, Xumin Huang, Maoqiang Wu, Sabita Maharjan, Shengli Xie, Yan Zhang. 2019

653 citations recorded by the source corpus.

The drastically increasing volume and the growing trend on the types of data have brought in the possibility of realizing advanced applications such as enhanced driving safety, and have enriched existing vehicular services through data sharing among vehicles and data analysis. Due to limited resources with vehicles, vehicular edge computing and networks (VECONs) i.e., the integration of mobile edge computing and vehicular networks, can provide powerful computing and massive storage resources. However, road side units that primarily presume the role of vehicular edge computing servers cannot be fully trusted, which may lead to serious security and privacy challenges for such integrated platforms despite their promising potential and benefits. We exploit consortium blockchain and smart contract technologies to achieve secure data storage and sharing in vehicular edge networks. These technologies efficiently prevent data sharing without authorization. In addition, we propose a reputation-based data sharing scheme to ensure high-quality data sharing among vehicles. A three-weight subjective logic model is utilized for precisely managing reputation of the vehicles. Numerical results based on a real dataset show that our schemes achieve reasonable efficiency and high-level of security for data sharing in VECONs.

Subfields: Artificial Intelligence, Electrical and Electronic Engineering, Information Systems

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Citations in the corpus

Incentive Design for Efficient Federated Learning in Mobile Networks: A Contract Theory Approach (2019, methodology): “For further work, we will consider using blockchains to ensure reliability of local model updates when formulating the incentive mechanism for reliable federated learning in mobile networks [17], [18], [19], [20].”
Blockchain Empowered Asynchronous Federated Learning for Secure Data Sharing in Internet of Vehicles (2020, methodology): “For instance, in [11], the authors exploited consortium blockchain, which is maintained by Road Side Units (RSUs) for achieving secure data sharing in vehicular edge networks.”
A Full Dive Into Realizing the Edge-Enabled Metaverse: Visions, Enabling Technologies, and Challenges (2022, background): “To solve this problem, the authors in [278] propose a consortium”
Toward Secure Blockchain-Enabled Internet of Vehicles: Optimizing Consensus Management Using Reputation and Contract Theory (2018, methodology): “[18] proposed a secure vehicle data sharing system in vehicular edge computing and networks, in which PoW consensus scheme is used for data sharing record”
Blockchain and Deep Reinforcement Learning Empowered Intelligent 5G Beyond (2019, methodology): “However, since a content usually involves much sensitive and critical personal information of its generator, caching requesters are not willing to store their contents with an untrusted caching provider [4].”
Evolutionary V2X Technologies Toward the Internet of Vehicles: Challenges and Opportunities (2020, methodology): “Consortium blockchain technologies together with smart contract were also used in [81] for secure data sharing and storage in vehicular edge networks.”
A Survey on Security and Privacy Issues in Edge-Computing-Assisted Internet of Things (2020, background): “[35] [10] [13] [37] [14] [8] [11] [36] [1] [6] [2] [15] [16] [17] [38] [39] [40] [12] [41] [5] [18] [42]”
Blockchain for Secure EHRs Sharing of Mobile Cloud Based E-Health Systems (2019, background): “To overcome such challenges, mobile edge cloud can be a promising solution to provide nearby health services to mobile users with low network latency [30].”
Permissioned Blockchain and Edge Computing Empowered Privacy-Preserving Smart Grid Networks (2019, background): “[37] combined edge computing technique with vehicular network to provide huge computing and storage resources and accepted consortium blockchain to guarantee secure data storage and sharing among vehicular edge computing networks.”
Edge Computing in Industrial Internet of Things: Architecture, Advances and Challenges (2020, background): “For instance, in IoV the security schemes of edge data sharing must be considered from all angles [92], [133], [134].”
Applications of Blockchains in the Internet of Things: A Comprehensive Survey (2019, background): “[117] propose a privacy preserving solution for secure data sharing in vehicular networks, with privacy preserving features.”
Blockchain for Internet of Things: A Survey (2019, background): “used to protect both the energy and information interactions between electric vehicles [92] and hybrid electric vehicles in smart grids [93], [94].”
Edge-computing-driven Internet of Things: A Survey (2022, methodology): “proposed to utilize consortium blockchain to establish a secure and distributed vehicular blockchain system for data management and storage by deploying smart contracts [84].”
Incentive Mechanism for Reliable Federated Learning: A Joint Optimization Approach to Combining Reputation and Contract Theory (2019, methodology): “We compare the proposed multiweight subjective logic scheme with a TSL scheme presented in [9] and [11].”
Blockchain for the Internet of Vehicles Towards Intelligent Transportation Systems: A Survey (2020, methodology): “in [86] utilizes consortium blockchain, where they introduce a blockchain-based secure and distributed data management system within the vehicular edge computing networks.”
Edge Computing with Artificial Intelligence: A Machine Learning Perspective (2022, methodology): “[44] use blockchain technology to protect the security of data storage and sharing.”
Healthchain: A Blockchain-Based Privacy Preserving Scheme for Large-Scale Health Data (2019, background): “Considering that Userchain is a public blockchain, as many schemes [18], [23] do, we”