Year: 2024
Type: conference-paper
Abstract: The rapid advancement of big data technology has heightened the prominence of personal information security concerns. Particularly within legal compliance, striking a balance between big data analysis and safeguarding personal privacy has emerged as an issue demanding resolution. Firstly, this paper discusses the challenges faced by personal information protection in the big data environment, and emphasizes the necessity of protecting personal information according to law. Then, a privacy protection technology based on a differential privacy algorithm is introduced. By adding noise to personal data, it can cover up sensitive information, thus effectively protecting personal privacy. To verify the actual effect of this method, a series of comparative experiments were designed and implemented. The results show that the proposed privacy algorithm effectively protects personal privacy and maintains data availability and accuracy. At the same time, it performs well with operational efficiency and model evaluation accuracy. This paper proposes a feasible privacy protection scheme, which provides a valuable reference for protecting personal information in big data applications. In addition, it emphasizes legal compliance in protecting personal information and provides direction for future research.
Author: Yineng Xiao
Institution: Nanjing University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Funder: Government of Jiangsu Province
OpenAlex ID: W4412524700