Blockchain-Based Internet of Vehicles (IoV): An Efficient Secure Ad Hoc Vehicular Networking Architecture

Sharma, Sachin; Ghanshala, Kamal Kumar; Mohan, Seshadri

doi:10.1109/5gwf.2019.8911664

Cited by 50 publications

(14 citation statements)

References 13 publications

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“…As regards works related to the Blockchain-based data management axis [105], [159], [323]- [354], [360], all contributions reside in both the IoV processing layer and IoV security layer to offer novel traffic services and/or secure the transferred data, thus avoiding the security attack of vehicular systems. Fundamental works propose the use of smart frameworks for generating, storing, and sharing data over existing network elements, including vehicles, users, infrastructure nodes, and sensors, over a consortium or private Blockchain [324], [328], [334], [340], [341], [344], [345], [358], [359]. As a primordial service for improving road safety, especially with the introduction of self-driving cars, a control application for accidents that aided in analyzing and verifying the cause of accidents was suggested in [324].…”

Section: Data Managementmentioning

confidence: 99%

“…A privacy scheme was then implemented to prove the correctness of collected and stored events as well as the registry of driver information. In [334], a distributed solution for intelligent vehicular transactions was modeled and studied to overcome the limitations of traditional data management solutions based on a centralized approach. In [344], an enhanced version of the Diffie-Hellman algorithm was proposed to improve trust on the applied verification mechanism in a consortium Blockchain-based network.…”

Section: Data Managementmentioning

confidence: 99%

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Blockchain Technology for Intelligent Transportation Systems: A Systematic Literature Review

Dhib²,

et al. 2022

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The use of Blockchain technology has recently become widespread. It has emerged as an essential tool in various academic and industrial fields, such as healthcare, transportation, finance, cybersecurity, and supply chain management. It is regarded as a decentralized, trustworthy, secure, transparent, and immutable solution that innovates data sharing and management. This survey aims to provide a systematic review of Blockchain application to intelligent transportation systems in general and the Internet of Vehicles (IoV) in particular. The survey is divided into four main parts. First, the Blockchain technology including its opportunities, relative taxonomies, and applications is introduced; basic cryptography is also discussed. Next, the evolution of Blockchain is presented, starting from the primary phase of pre-Bitcoin (fundamentally characterized by classic cryptography systems), followed by the Blockchain 1.0 phase, (characterized by Bitcoin implementation and common consensus protocols), and finally, the Blockchain 2.0 phase (characterized by the implementation of smart contracts, Ethereum, and Hyperledger). We compared and identified the strengths and limitations of each of these implementations. Then, the state of the art of Blockchain-based IoV solutions (BIoV) is explored by referring to a large and trusted source database from the Scopus data bank. For a well-structured and clear discussion, the reviewed literature is classified according to the research direction and implemented IoV layer. Useful tables, statistics, and analysis are also presented. Finally, the open problems and future directions in BIoV research are summarized.

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Section: Data Managementmentioning

confidence: 99%

Section: Data Managementmentioning

confidence: 99%

Blockchain Technology for Intelligent Transportation Systems: A Systematic Literature Review

Dhib²,

et al. 2022

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“…Previous works utilize blockchain-based mechanisms (e.g. [41]) to address the data privacy issues. However, there is still a huge gap before striking a balance between sensitive data utility and privacy in the context of IoV.…”

Section: Takeaways From Brook Dataset and Example Studiesmentioning

confidence: 99%

BROOK Dataset: A Playground for Exploiting Data-Driven Techniques in Human-Vehicle Interactive Designs

Jin¹,

Duan²,

Liu³

et al. 2022

Preprint

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Emerging Autonomous Vehicles (AV) breed great potentials to exploit data-driven techniques for adaptive and personalized Human-Vehicle Interactions. However, the lack of high-quality and rich data supports limits the opportunities to explore the design space of data-driven techniques, and validate the effectiveness of concrete mechanisms. Our goal is to initialize the efforts to deliver the building block for exploring data-driven Human-Vehicle Interaction designs. To this end, we present BROOK dataset, a multi-modal dataset with facial video records. We first brief our rationales to build BROOK dataset. Then, we elaborate how to build the current version of BROOK dataset via a year-long study, and give an overview of the dataset. Next, we present three example studies using BROOK to justify the applicability of BROOK dataset. We also identify key learning lessons from building BROOK dataset, and discuss about how BROOK dataset can foster an extensive amount of follow-up studies. INTRODUCTIONRecent advances in data-driven techniques (e.g. Neural Networks) breed an extensive amount of opportunities, to enable adaptive and personalized Human-Vehicle Interaction (HVI). More interestingly, the emerging trends of Autonomous Vehicles relax the conventional burdens of driving, and in-vehicle drivers/passengers are capable to obtain better user experiences through more complex HVI. Incorporating data-driven approaches can greatly improve user experiences during driving processes. For instance, unobtrusive monitors of multi-modal statuses (i.e. by taking alternative data sources as input), rather than directly equipping biosensors, are more user-friendly as data sources for personalized interaction between drivers and vehicles. Therefore, combining data-driven techniques with HVI becomes promising in the near future, and relevant datasets become essential and highly demanded.Though there are already several datasets for HVI, there are four major limitations of existing datasets. First, the design purposes of existing datasets focus on a specific type of study purposes (e.g. Stress Detection [20], Driving Workload [40] and etc.), which naturally limits their potentials due to the narrowly-selected types of data streams. Second, existing datasets only collect information

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“…In particular, video data collected by cameras, such as traffic accident information and road condition information, need to be transmitted to other nodes through mobile video communication technology. However, in the process of communication between the nodes in the VANETs, security and privacy are the main concerns [1], including the security protection issues (such as integrity and correctness) of the VANETs data in transmission process, the security issues (such as non-tampering) of VANETs data stored in the data center, the access control issues (such as identity verification), and privacy protection issues.…”

Section: Introductionmentioning

confidence: 99%

“…At present, there have been many studies on using blockchain in the VANETs environment, mainly including the architecture [1][2][3][4], authentication mechanism [5][6][7], privacy protection [8][9][10], trust management [11][12][13], certificate management [14,15], and data sharing [16][17][18].…”

Section: Introductionmentioning

confidence: 99%

V-Lattice: A Lightweight Blockchain Architecture Based on DAG-Lattice Structure for Vehicular Ad Hoc Networks

Zhang

Hou

et al. 2021

Security and Communication Networks

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With the development of wireless communication technology and the automobile industry, the Vehicular Ad Hoc Networks bring many conveniences to humans in terms of safety and entertainment. In the process of communication between the nodes, security problems are the main concerns. Blockchain is a decentralized distributed technology used in nonsecure environments. Using blockchain technology in the VANETs can solve the security problems. However, the characteristics of highly dynamic and resource-constrained VANETs make the traditional chain blockchain system not suitable for actual VANETs scenarios. Therefore, this paper proposes a lightweight blockchain architecture using DAG-lattice structure for VANETs, called V-Lattice. In V-Lattice, each node (vehicle or roadside unit) has its own account chain. The transactions they generated can be added to the blockchain asynchronously and parallelly, and resource-constrained vehicles can store the pruned blockchain and execute blockchain related operations normally. At the same time, in order to encourage more nodes to participate in the blockchain, a reputation-based incentive mechanism is introduced in V-Lattice. This paper uses Colored Petri Nets to verify the security of the architecture and verifies the feasibility of PoW anti-spam through experiment. The validation results show that the architecture proposed in this paper is security, and it is feasible to prevent nodes from generating malicious behaviors by using PoW anti-spam.

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Blockchain-Based Internet of Vehicles (IoV): An Efficient Secure Ad Hoc Vehicular Networking Architecture

Cited by 50 publications

References 13 publications

Blockchain Technology for Intelligent Transportation Systems: A Systematic Literature Review

Blockchain Technology for Intelligent Transportation Systems: A Systematic Literature Review

BROOK Dataset: A Playground for Exploiting Data-Driven Techniques in Human-Vehicle Interactive Designs

V-Lattice: A Lightweight Blockchain Architecture Based on DAG-Lattice Structure for Vehicular Ad Hoc Networks

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