Decentralized and Efficient Differential Private Mechanisms in Blockchain-based System

As an emerging technology, blockchain has attracted widespread attention from academia and industry. However, the decentralization and transparency features bring some privacy issues to the users. The adversary can obtain the sensitive chain data via a malicious node or several queries. To address these issues, this thesis proposes decentralized and efficient differential private mechanisms to preserve users' privacy in diverse blockchain-based scenarios. In addition, this thesis analyzes the problems in post-processing and proposes a controllable solution to conduct limited perturbation. The experiment results indicate the proposed solutions provide both a privacy guarantee and better utility than the traditional approaches.