Privacy-Preserving Data Sharing In Decentralized Systems

Abstract

Protecting sensitive data, such as medical records, necessitates privacy-preserving data sharing in decentralized systems. This abstract delves into the fusion of Differential Privacy (DP) and Advanced Encryption Standard (AES) encryption methods to fortify data security. AES encryption is pivotal in transforming medical records into an unintelligible format accessible onl[1]y with the correct decryption key, ensuring data confidentiality. Simultaneously, DP introduces an additional layer of privacy by injecting noise into query responses, thwarting the extraction of personal data while enabling insightful analysis.

This approach safeguards patient privacy while preserving data utility for healthcare research and analysis in decentralized systems by amalgamating DP and AES encryption. The proposed methodology offers a pragmatic solution to the intricate conundrum of balancing data sharing and privacy, guaranteeing the integrity and confidentiality of private health information in decentralized settings. This framework serves as a foundational pillar for secure and ethical healthcare practices in the digital era, adept at addressing the evolving challenges associated with data sharing while upholding privacy.