Combining Cryptography and Other Techniques for Various Privacy-Preserving Applications

Abstract. Secure multiparty computation (SMPC), fully homomorphic encryption (FHE) and differential privacy (DP) is a selection of Privacy-Enhancing Technologies (PETs) that protect input data confidentiality and enable the computation of a function without revealing the input data. Using PETs, one can keep sensitive data private and at the same time derive valuable insights from data analysis, optimizing the privacy-utility tradeoff. In this talk, we will introduce and compare different PETs in order to assist in selecting the most suitable options for a given application and show that they aren't a one-size-fits-all solution. We will present two applications, the first one is genomic data machine learning and second one is financial fraud detection.

Suggested readings: Suggested readings: ia.cr/2021/733, doi:10.1007/s00145-023-09464-4, HyPETs workshop