Date : June 9, 2022, 3 p.m. - Room :Salle du conseil

Towards privacy-preserving and trustworthy AI

Melek Önen, Maître de conférence - EURECOM Sophia Antipolis

Machine Learning as a Service (MLaaS) provides stakeholders the ease to perform (computationally-intensive) machine learning tasks on a third-party cloud platform. This advantage of outsourcing these operations, unfortunately comes with a high cost in terms of privacy exposures. The goal is therefore to come up with customized ML algorithms that would by design preserve the privacy of the processed data. Advanced cryptographic techniques such as fully homomorphic encryption or secure multi-party computation enable the execution of some operations over encrypted data and therefore can be considered as potential candidates for these algorithms. Yet, these incur high computational and/or communication costs for some operations. In this talk, we will analyze the tension between ML techniques and relevant cryptographic tools. We will further overview existing solutions addressing both privacy and trust requirements.