@article{4582,
  author = {Bing Xu, Yu Song },
  title = {Enhancing Cloud Accounting Security: A Rough Set-Based Parallel Algorithm for Efficient Data Integrity Verification},
  journal = {Journal of Information Technology Review},
  year = {2025},
  volume = {16},
  number = {4},
  doi = {https://doi.org/10.6025/jitr/2025/16/4/138-145},
  url = {https://www.dline.info/jitr/fulltext/v16n4/jitrv16n4_2.pdf},
  abstract = {This paper proposes a rough set-based data mining algorithm to enhance data integrity verification within cloud-based accounting information systems. It addresses security risks inherent in cloud storage, such as data breaches and corruption, which traditional verification methods handle inefficiently due to high computational and bandwidth costs. The authors introduce a novel parallel verification algorithm that can simultaneously check data for single or multiple users, significantly reducing communication time and computational overhead compared to single point testing. Experimental results demonstrate that this approach, leveraging cloud computing’s parallel processing capabilities, greatly improves computational efficiency and reduces update costs while ensuring data completeness. The system also allows users to select different audit levels, balancing verification speed, precision, and cost. The research aims to provide a more secure and efficient framework for financial data management in the era of accounting informationization.},
}