Stealth Announces New Result in Privacy-preserving Machine Learning at ISC ’19
Sep 2, 2019
As part of the PULSAR and PANTHEON projects, Stealth team member Vassilis Zikas (Edinburgh), in collaboration with Maksim Tsikhanovich (Amazon and Edinburgh), Malik Magdon-Ismail (Edinburgh), and Muhammad Ishaq (Edinburgh), presented their work on “PD-ML-Lite: Private Distributed Machine Learning from Lightweight Cryptography” at the 2019 Information Security Conference. A link to the corresponding publication (in the conference proceedings) can be found here.