Key points are not available for this paper at this time.
With the rapid advancement of digital twin (DT) technology and the proliferation of IoT devices, ensuring secure and privacy-preserving access control for sensitive data has become a critical challenge. While blockchain provides a decentralized and tamper-proof solution for data integrity, its transparency raises privacy concerns when handling access policies and user attributes in traditional ciphertext-policy attribute-based encryption (CP-ABE) schemes. Existing approaches struggle to balance privacy protection, computational efficiency, and scalability, particularly for resource-constrained IoT environments. In this paper, we propose a blockchain-based, privacy-preserving access control scheme that integrates an optimized hidden policy CP-ABE with multiplicative homomorphic encryption to achieve secure and efficient data sharing in digital twin systems. First, our scheme enhances policy privacy while supporting large-universe attribute sets, addressing the inefficiency of conventional hidden policy CP-ABE schemes by eliminating bilinear pairing operations on the resource-constrained device side. Second, we leverage the multiplicative homomorphic properties of the ElGamal cryptosystem to protect attribute privacy during authentication, preventing leakage to intermediaries or malicious blockchain nodes. Finally, we formally prove the security of our scheme under indistinguishability against chosen-plaintext attack (IND-CPA) security model and the implementation and evaluation are conducted to analyze its efficiency.
Wang et al. (Thu,) studied this question.