A fine-grained, controllable blockchain rewriting method with a hidden strategy for user tracking, revocation, and attribute cancellation under cloud computing.
By employing a hidden strategy that allows for user tracking, revocation, and attribute cancellation in the blockchain, this fine-grained and controllable blockchain rewriting method utilizes chameleon hashing and outsourced computation technology to solve the problem of data correction in multi-user environments of blockchain systems. This method achieves fine-grained and controllable data rewriting and tracking and cancellation of malicious users, thereby improving the security and scalability of the blockchain.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- SHANXI UNIV
- Filing Date
- 2026-02-12
- Publication Date
- 2026-05-26
AI Technical Summary
Blockchain systems lack effective means to legally correct data in multi-user collaborative environments, especially when there are erroneous records, sensitive information leaks, or illegal content, making it impossible to correct data without disrupting the overall structural consistency of the chain.
This paper proposes a fine-grained, controllable blockchain rewriting method that employs a hidden strategy that allows for user tracking, revocation, and attribute reversal. By replacing traditional hash functions with a policy-based chameleon hash (PCH) and combining it with outsourced computation technology, the method enables attribute verification and key management for data modifiers, supporting fine-grained, controllable data rewriting and tracking and revocation of malicious users.
It enables fine-grained, controllable, and rewritable blockchain, improves algorithm efficiency, reduces user burden, enhances data privacy protection, supports attribute revocation and malicious user tracking, ensures that data modifiers can only modify data when access policies are met, and improves the security and scalability of the blockchain.
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