Cryptography-Based Privacy-Preserving Data Analysis and Empowering Data Privacy through Secure Multi-Party Computation: Challenges and Solutions
Abstract
The conflict between the necessity of data analysis and the preservation of personal privacy is greater than ever in today's data-driven society. This conference paper offers a comprehensive examination of privacy-preserving data analysis, illuminating the methods, difficulties, and solutions related to this crucial nexus. The article begins with a "Introduction," which highlights the rising worries about data privacy and breaches and establishes the value of data analysis in numerous sectors, including healthcare, finance, and social sciences. It emphasises how important privacy protection is, particularly in situations involving collaborative data analysis when several parties contribute data without jeopardising individual privacy. The study concludes with a discussion of "Practical Challenges in Secure MPC Implementation," which emphasises the practicalities of using privacy-preserving data analysis methods in everyday situations. It emphasises how crucial safe setup, knowledge of cryptography, and data pretreatment are. In summary, this conference paper provides readers with a clearer grasp of the difficulties and approaches involved in striking a balance between the demands of data analysis and data privacy by providing a thorough review of privacy-preserving data analysis. It is meant to be an important tool for academics, professionals, and organisations that want to use data to its full potential while protecting people's right to privacy.