🤖 AI Summary
To address the trade-off among efficiency, security, and dynamic scalability in Revocable Attribute-Based Encryption (RABE) schemes for IoT cloud storage, this paper proposes an efficient RABE scheme. Our method fully delegates user revocation operations to the cloud and achieves multi-challenge ciphertext security under an adaptive security model. Furthermore, it integrates a lightweight integrity verification mechanism to support fine-grained access control and dynamic user revocation. The scheme significantly reduces computational overhead on resource-constrained IoT devices: experimental results show that encryption and decryption times are reduced by 7–9× compared to state-of-the-art RABE schemes under identical access policies. The design preserves strong security guarantees, functional completeness—including expressive access structures and immediate revocation—while respecting stringent IoT device resource constraints.
📝 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.