Data Privacy Research

Data privacy research is the investigation of mathematical, cryptographic, and organizational techniques to protect personal data while enabling useful computation and analytics. Core topics: differential privacy (statistical guarantees), k-anonymity (hard to re-identify), homomorphic encryption (compute on ciphertexts), federated learning (decentralized training). Example: How can a hospital analyze patient records to detect disease patterns without exposing individual patients? Use differential privacy: add noise so no single patient's data changes the result.