Stealth Announces New Result in Privacy-preserving Machine Learning at ISC ’19

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.