The 2024 CNIL Annual Report presents an overview of the state of personal data protection in France. It highlights key trends, the evolution of practices, and the main actions in regulation, enforcement, and guidance conducted by the CNIL over the past year. The report also addresses major challenges related to digital transformation, AI, cybersecurity, and the protection of citizens’ rights in the digital age.
This comprehensive study examines methods for developing machine learning systems that protect individual privacy while maintaining high performance. The research analyzes various privacy-preserving techniques including differential privacy, federated learning, and secure multi-party computation. The authors provide practical guidelines for implementing privacy-preserving ML systems and evaluate the trade-offs between privacy guarantees and model utility. The paper also addresses emerging challenges in privacy-preserving ML, including new attack vectors and regulatory compliance requirements.