Differential Privacy: Achieving Privacy-preserving Data Publishing

This lecture delves into the concept of differential privacy, focusing on achieving privacy-preserving data publishing through input and output perturbation techniques. The instructor explains the principles of differential privacy, the challenges in achieving it, and practical examples of its implementation. Topics covered include differential privacy properties, input perturbation methods, output perturbation techniques, and the randomised response algorithm. The lecture also discusses the utility-privacy trade-off, privacy budget management, and the importance of composition and post-processing theorems in practice.