EDDAC: An Efficient and Decentralized Data Access Control Scheme With Attribute Privacy Preservation | IEEE Journals & Magazine | IEEE Xplore

EDDAC: An Efficient and Decentralized Data Access Control Scheme With Attribute Privacy Preservation


Abstract:

The rapid development of the Internet of Things (IoT) has led to the generation and perception of large amounts of data from IoT devices. These data are outsourced to the...Show More

Abstract:

The rapid development of the Internet of Things (IoT) has led to the generation and perception of large amounts of data from IoT devices. These data are outsourced to the cloud for flexible sharing and deep analytics, which can significantly enhance IoT applications. But this raises privacy concerns for IoT devices. Attribute-based encryption is applied to realize fine-grained access control, which offers data owners control capability over their outsourced data. However, the centralized infrastructure is susceptible to the single-point-of-failure problem and may not be suitable for highly distributed IoT applications due to high latency. To overcome this issue, blockchain technology is introduced to realize a distributed infrastructure and provide robust data services. Owing to the innate transparency characteristic of blockchain, challenges associated with privacy are amplified. Therefore, this article presents an efficient and decentralized data access control (EDDAC) scheme that preserves attribute privacy. The scheme utilizes chameleon hash to implement attribute hiding, providing resistance against dictionary attacks. Additionally, it includes blockchain-based decryption tests that reduce the decryption overhead on clients through the application of inner product predicate encryption. Furthermore, our scheme employs Shamir secret sharing to achieve decentralized authorization based on blockchain, thereby reducing the trust-building overhead on authorization nodes. Finally, we provide proof of the adaptive security of the proposed scheme and demonstrate its effectiveness and advantages through simulations and comparisons with existing literature.
Published in: IEEE Internet of Things Journal ( Volume: 11, Issue: 8, 15 April 2024)
Page(s): 14579 - 14592
Date of Publication: 13 December 2023

ISSN Information:

Funding Agency:


References

References is not available for this document.