Under the digital prosecutorial strategy, procuratorial organs promote digital prosecutorial reform by deeply integrating technological innovations such as big data and artificial intelligence, establishing legal supervision models and supporting systems, and discovering and promoting the cracking of deep-seated problems in law enforcement, judicial activities, and social governance. In practice, the data relied on by supervisory models, algorithms, and systems often goes beyond the scope of internal data in prosecution and case handling. Efficient and secure data sharing is an important part of doing a good job in prosecution and case handling. From a policy perspective, the central government has clear requirements for judicial data sharing. In 2021, the Central Political and Legal Commission issued the "Guiding Opinions on Fully Utilizing Intelligent Means to Promote the Long term Treatment of Persistent Diseases in the Political and Legal System", which clearly requires "improving the cross departmental sharing mechanism of law enforcement and judicial data", and proposes innovative measures to break data barriers such as building a "cross departmental big data case handling platform". However, the issue of data sharing has not been fully resolved, and situations of unwillingness to share, reluctance to share, or even inability to share data often occur. From the perspective of sharing entities, most existing big data legal supervision platforms are applied within procuratorial organs, with few cross unit and cross system platforms. Even if external units participate, they are often limited to judicial law enforcement agencies, and administrative agencies have low enthusiasm; From the perspective of the types of data accessed by the platform, the vast majority come from internal data of prosecutorial business application systems, mainly serving the goals of improving prosecutorial case handling efficiency and strengthening internal supervision and management. External data is relatively scarce, making it difficult to fully leverage the collaborative social governance function of digital prosecution; From the perspective of data security, issues such as data security and privacy protection are not only abstract technical issues, but also practical subject responsibilities. After the data was collected on the big data legal supervision platform, the data users changed, but the responsible parties were not completely transferred. The root cause of the aforementioned dilemma is mainly the limitations of data sharing mechanisms. The existing big data legal supervision platforms mostly adopt a platform centered data sharing mechanism, where data from all parties is gathered into the procuratorial business application system, and procuratorial organs rely on the platform to carry out digital procuratorial work. This platform centric model has certain advantages in centralized data management, but it can easily raise concerns among relevant parties about data ownership, usage rights, and related privacy issues. At the same time, due to the misalignment of data rights and responsibilities, the platform centric model is difficult to spontaneously form by data sharing entities, but highly relies on top-down administrative driving. To further improve the data sharing mechanism, it is necessary to address pain points and eliminate concerns in the underlying logic of the sharing mechanism. Transforming from a platform centric model to a decentralized data sharing model can help solve the difficulties faced by data sharing from the source. In terms of architecture design, collaborative processing of multi-source heterogeneous data can be achieved while ensuring data security and data rights. Specifically, the decentralized data sharing model consists of a platform layer, data layer, and application layer as its basic framework. The platform layer consists of a data station and an unspecified number of data nodes, connected through a network. In the data sharing system of digital prosecution, the big data legal supervision platform is a data station, and each unit (department) participating in data sharing can be seen as a data node, data station, and