A Fine-Grained Data Access Control Scheme With Policy Privacy and Attribute Privacy in Vehicle-to-Grid

The Vehicle-to-Grid (V2G) network facilitates secure, fine-grained access control of sensitive data through Attribute-Based Encryption (ABE), where policy privacy and attribute privacy are two significant design concerns. However, achieving both forms of privacy presents a trade-off between privacy and efficiency. While integrating policy and attribute privacy can provide comprehensive protection, it requires costly O(n) communication overhead and necessitates the negotiation of blinding factors between data owners and users–contradicting the fundamental principles of ABE. This raises an essential question: How to achieve efficient integration of attribute and policy privacy without compromising fine-grained control? This paper propose a novel scheme that leverages vectorial orthogonality to enable efficient matching between attributes and policies. By applying orthogonality, it allows attribute and policy blinding to skip de-blinding during decryption, eliminating the need for prenegotiated blinding parameters. This approach preserves the finegrained properties of ABE without additional communication overhead. To address security challenges associated with privacypreserving operations, this paper further incorporate vector commitment, enabling public verifiability and preventing unauthorized access. It also formally proves that this scheme achieves adaptive chosen-plaintext security under the standard model. Performance analysis demonstrates that, this scheme reduces the reliance on pairing and exponential operations, making it efficient and practical for V2G applications.