1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.CR2024★ 1 cited
A Pervasive, Efficient and Private Future: Realizing Privacy-Preserving Machine Learning Through Hybrid Homomorphic Encryption
Khoa Nguyen, Mindaugas Budzys, Eugene Frimpong +2
Machine Learning (ML) has become one of the most impactful fields of data science in recent years. However, a significant concern with ML is its privacy risks due to rising attacks…
cs.SI2022
MetaPriv: Acting in Favor of Privacy on Social Media Platforms
Robert Cantaragiu, Antonis Michalas, Eugene Frimpong +1
Social networks such as Facebook (FB) and Instagram are known for tracking user online behaviour for commercial gain. To this day, there is practically no other way of achieving pr…