Differential Privacy: A Robust Mechanism for Protecting Sensitive Information in the AI Era

Differential Privacy (DP) protects data by adding noise to queries, preventing re-identification while maintaining utility, and addresses the privacy challenges of the artificial intelligence era. Traditional anonymization techniques, such as pseudonymization and k-anonymity, have proven insufficient against sophisticated re-identification attacks. DP is a robust privacy-preserving mechanism that is crucial in a context where privacy and security are becoming major challenges.