4 citations · 4 across the 4 of their papers we have counts for
4 papers
Make Split, not Hijack: Preventing Feature-Space Hijacking Attacks in Split Learning
Tanveer Khan, Mindaugas Budzys, Antonis Michalas
The popularity of Machine Learning (ML) makes the privacy of sensitive data more imperative than ever. Collaborative learning techniques like Split Learning (SL) aim to protect cli…
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…
Split Without a Leak: Reducing Privacy Leakage in Split Learning
Khoa Nguyen, Tanveer Khan, Antonis Michalas
The popularity of Deep Learning (DL) makes the privacy of sensitive data more imperative than ever. As a result, various privacy-preserving techniques have been implemented to pres…
Split Ways: Privacy-Preserving Training of Encrypted Data Using Split Learning
Tanveer Khan, Khoa Nguyen, Antonis Michalas
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…