6 papers
From See to Shield: ML-Assisted Fine-Grained Access Control for Visual Data
Mete Harun Akcay, Buse Gul Atli, Siddharth Prakash Rao +1
As the volume of stored data continues to grow, identifying and protecting sensitive information within large repositories becomes increasingly challenging, especially when shared…
Love or Hate? Share or Split? Privacy-Preserving Training Using Split Learning and Homomorphic Encryption
Tanveer Khan, Khoa Nguyen, Antonis Michalas +1
Split learning (SL) is a new collaborative learning technique that allows participants, e.g. a client and a server, to train machine learning models without the client sharing raw…
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…
Heal the Privacy: Functional Encryption and Privacy-Preserving Analytics
Alexandros Bakas, Antonis Michalas
Secure cloud storage is an issue of paramount importance that both businesses and end-users should take into consideration before moving their data to, potentially, untrusted cloud…
Blind Faith: Privacy-Preserving Machine Learning using Function Approximation
Tanveer Khan, Alexandros Bakas, Antonis Michalas
Over the past few years, a tremendous growth of machine learning was brought about by a significant increase in adoption of cloud-based services. As a result, various solutions hav…
Attestation Waves: Platform Trust via Remote Power Analysis
Ignacio M. Delgado-Lozano, Macarena C. Martínez-Rodríguez, Alexandros Bakas +2
Attestation is a strong tool to verify the integrity of an untrusted system. However, in recent years, different attacks have appeared that are able to mislead the attestation proc…