Protection Method of Network Data Privacy Security Issues Based on Blockchain Technology

Abstract

As a new model of Internet-based computers, blockchain technology has always been a hot spot for scholars and the industry. Although blockchain technology has been developed for many years, data security and reliable computing are still the main challenges facing the current blockchain technology applications. In order to solve this problem, many researchers have conducted a lot of research on it and proposed many models, including data integrity verification and secure multi-part calculation. However, most of these solutions face problems such as high computational complexity or lack of scalability. This paper proposes a data release method based on differential privacy protection for the problems of the release of static data sets and the release of dynamic data, and uses the built platform for experimental verification. Aiming at the privacy leakage problem faced by the multi-level and fine-grained search of big data, this paper proposes an incremental data indexing strategy based on conceptual lattice granular deduction, and builds a complete data retrieval service system that supports differentiation on the cloud platform architecture, it also supports practical search modes such as multi-keyword ranking search, similarity search and fuzzy search, and systematic research on the protection methods of network data privacy security issues under blockchain technology. The experimental results surface: Compared with other methods, the algorithm in this paper has greatly reduced information loss under the same privacy requirements, and the algorithm has high execution efficiency. This shows that the results of this study can provide ideas for the research of big data security and privacy protection, and have certain reference significance.