Design And Implementation Of Data Auditing Based On Operational Dynamics

As a data storage system,the big data sharing platform provides data storage and sharing services to different institutions and departments.These data include various structures,including raw data,semi-structured data,and structured data.The goal of the platform is to improve data utilization efficiency and value,but it faces challenges such as data security,user privacy,and data leakage in achieving its objectives.Data auditing plays a crucial role in addressing these data security issues.Through data auditing,data accuracy and reliability can be ensured to avoid the impact of incorrect data on decision-making.At the same time,data auditing can also ensure that data access and use comply with privacy regulations and prevent security risks such as data leakage.To address the challenges faced by data auditing in data sharing platforms and to solve the single-point failure problem of data auditing systems,a blockchain-based data audit scheme is proposed.To identify malicious user data audit requests,an identity verification mechanism based on Pederson commitments is proposed.Based on Pederson’s hiding property,binding property,and homomorphic property,the anonymity of the user’s real identity is achieved,and the correctness of identity verification is ensured.To achieve historical traceability of audit data,a new data structure called Audit Token(AToken)is designed.AToken stores information such as the type of data audit operation,time,and digital signature.To more efficiently verify the validity of AToken,a dualcounting Bloom filter is designed.The dual-counting Bloom filter not only saves storage space but also greatly reduces the false positive rate of the counting bloom filter.Based on the above scheme,this paper designs a three-tier data audit system(TDAS)consisting of a data layer,a system layer,and a user layer.The data layer is mainly responsible for storing AToken generated by the system.The main storage media include blockchain node Peers and Counting Bloom Filters(CBF).The system layer is responsible for interaction with the data layer and the user layer and implements the audit module based on smart contracts,including data auditing and AToken validity verification mechanism.The user layer is responsible for implementing the web application interface of the TDAS system and provides interfaces for TDAS and user interaction,including service registration and identity authentication interfaces.Finally,this paper analyzes the performance of TDAS.The results show that TDAS has low latency and requires less computational resources.These results provide strong evidence for the feasibility and practicality of TDAS.