Bibliographic Details
| Title: |
Blockchain-enabled efficient distributed attribute-based access control framework with privacy-preserving in IoV |
| Authors: |
Ye Zhang, Leyou Zhang, Qing Wu, Yi Mu |
| Source: |
Journal of King Saud University: Computer and Information Sciences, Vol 34, Iss 10, Pp 9216-9227 (2022) |
| Publisher Information: |
Elsevier, 2022. |
| Publication Year: |
2022 |
| Collection: |
LCC:Electronic computers. Computer science |
| Subject Terms: |
IoV, Privacy protection, Attribute-based encryption, Blockchain, Electronic computers. Computer science, QA75.5-76.95 |
| More Details: |
Aiming at solving the challenges of the Internet of Vehicles (IoV), such as privacy sensitive data exposing, data being vulnerable to unauthorized access and tampered with and the single point of failure of the cloud server, this paper introduces a blockchain-enabled data access method based on attribute-based encryption. To enhance the privacy protection, the attributes are hidden and all generated transactions are recorded on the blockchain for auditing. Even if it is untrusted to a third party, it can guarantee the user’s control over his own data. To reduce the computation cost, decentralized edge nodes jointly maintain the blockchain and assist users with limited resources to complete most of the calculations. Meanwhile, the use of smart contracts not only reduces the verification workload, but also evaluates multiple factors such as the communication range, communication time, and calculation overhead of the roadside unit (RSU) to ensure that the vehicle can receive messages in a timely manner. In addition, timely updating the attributes can reduce the user’s computational burden and increase the flexibility of the system. Numeral experiments to show the proposed scheme has many advantages of over others such as the storage cost, the whole time consume of the proposed algorithms and the proxy computation cost. |
| Document Type: |
article |
| File Description: |
electronic resource |
| Language: |
English |
| ISSN: |
1319-1578 |
| Relation: |
http://www.sciencedirect.com/science/article/pii/S1319157822003251; https://doaj.org/toc/1319-1578 |
| DOI: |
10.1016/j.jksuci.2022.09.004 |
| Access URL: |
https://doaj.org/article/60f6e6afe2a74c42a9ef61256146da6c |
| Accession Number: |
edsdoj.60f6e6afe2a74c42a9ef61256146da6c |
| Database: |
Directory of Open Access Journals |
