Fast Revocable Attribute-Based Encryption with Data Integrity for Internet of Things

• URL: http://arxiv.org/abs/2509.20796v1
• Date: Thu, 25 Sep 2025 06:24:29 GMT
• Title: Fast Revocable Attribute-Based Encryption with Data Integrity for Internet of Things
• Authors: Yongjiao Li, Liang Zhu, Yalin Deng, Qikun Zhang, Zhenlei Wang, Zhu Cao,
• Abstract summary: revocable-based encryption (RABE) is vital for ensuring flexible and fine-grained access control and data sharing in cloud storage and outsourced data environments within the Internet of Things (IoT)<n>We propose a fast RABE scheme with data integrity for IoT that attributes adaptive security with multiple challenge ciphertexts.<n>We have demonstrated its adaptive security within the defined security model with multiple challenge ciphertexts and optimized its performance.
• Score: 8.62717748522007
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Efficient and secure revocable attribute-based encryption (RABE) is vital for ensuring flexible and fine-grained access control and data sharing in cloud storage and outsourced data environments within the Internet of Things (IoT). However, current RABE schemes often struggle to achieve an optimal balance between efficiency, security, dynamic scalability, and other important features, which hampers their practical application. To overcome these limitations, we propose a fast RABE scheme with data integrity for IoT that achieves adaptive security with multiple challenge ciphertexts. Our scheme supports the revocation of authorized users and transfers the computationally heavy revocation processes to the cloud, thereby easing the computational burden on IoT devices. Moreover, it consistently guarantees the integrity and correctness of data. We have demonstrated its adaptive security within the defined security model with multiple challenge ciphertexts and optimized its performance. Experimental results indicate that our scheme provides better performance than existing solutions. Under the same access policy, our scheme reduces computational consumption by 7 to 9 times compared to previous schemes.

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