Trusted Blockchain-based Data Fingerprinting Differential-Traceability and SkipList Indexing Methods in Privacy Protection

Abstract

The process of data interaction is often criticized by the public for data privacy leakage, attribution disputes, as well as being maliciously tampered with and difficult to trace the source of data. This paper proposes a data privacy protection and fingerprint tracing method based on the features of decentralization, traceability and non-tampering in blockchain technology. And we combined with the protection of data by secure network platform in trusted computing and differential-traceability algorithm (DTA). We propose a data privacy protection and fingerprint traceability method, and use the SkipList table index structure to improve interaction efficiency. We discuss the proposed data fingerprint-based traceability framework model in a trusted environment using the features of blockchain and trusted computing platforms. In this paper, the data can be processed safely and efficiently to solve the privacy problem, the transaction data is encrypted and recorded on the chain by DTA, and the interaction process uses the SkipList table index to enhance retrieval efficiency. Finally, through multiple experiments and comparison of the results obtained from security testing, it is verified that the blockchain-trusted computing data privacy protection and data fingerprint traceability SkipList table indexing method can achieve traceability for data privacy protection, transaction security management and peer-to-peer verification of encryption and decryption algorithms. We not only provide a secure, trustworthy and efficient data privacy protection model, but also bring a time efficiency optimization of 6ms per 10,000 queries.