Book chapter
Polynomial-Based Revocation for Attribute-Based Access Control in Secure Cloud Data Sharing
Web and Big Data, pp 605-620
2027
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Abstract
With the widespread adoption of cloud computing, Ciphertext-Policy Attribute-Based Encryption (CP-ABE) has become a promising primitive for fine-grained access control over outsourced data. However, efficient attribute revocation remains a challenging issue in dynamic cloud data sharing, especially when a specific attribute of a user becomes invalid while the user’s other attributes and the same attribute held by other users remain valid. Existing revocation mechanisms often require secret-key updates for non-revoked users, ciphertext re-encryption, or additional update metadata, which limits their scalability in practical cloud environments. In this paper, we propose PBER-ABE, a polynomial-based and efficiently revocable CP-ABE scheme for secure cloud data sharing. The proposed scheme associates each attribute with a selector polynomial over the authorized user set and defines revocation over user-attribute pairs. Using compact coefficient commitments, the cloud server can update only the affected ciphertext components during revocation and reactivation, without learning the plaintext or requiring non-revoked users to update their long-term secret keys. We also incorporate an attribute authentication mechanism to protect user identity privacy and prevent impersonation attacks. The security analysis shows that PBER-ABE achieves data confidentiality, forward and backward security, and resistance to collusion attacks. Theoretical analysis and experimental results demonstrate that PBER-ABE provides efficient revocation and low user-side decryption overhead, making it suitable for large-scale and fine-grained cloud data sharing.
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Details
- Title
- Polynomial-Based Revocation for Attribute-Based Access Control in Secure Cloud Data Sharing
- Creators
- Yanyang Meng - Hebei UniversityMeng Wang - Hebei UniversityZhibo Sun - Drexel UniversityDelei Wang - Hebei UniversityHong Zhang - Hebei University
- Contributors
- Lingling Ding (Editor)Yannis Manolopoulos (Editor)Richard Chbeir (Editor)Karam Bou-chaaya (Editor)Schahram Dustdar (Editor)Tran Ngoc Tuan (Editor)
- Publication Details
- Web and Big Data, pp 605-620
- Series
- Lecture Notes in Computer Science
- Publisher
- Springer Nature; Singapore
- Resource Type
- Book chapter
- Language
- English
- Academic Unit
- Computer Science
- Other Identifier
- 991022232714804721