4 papers
Oops!... They Stole it Again: Attacks on Split Learning
Tanveer Khan, Antonis Michalas
Split Learning (SL) is a collaborative learning approach that improves privacy by keeping data on the client-side while sharing only the intermediate output with a server. However,…
A Privacy-Centric Approach: Scalable and Secure Federated Learning Enabled by Hybrid Homomorphic Encryption
Khoa Nguyen, Tanveer Khan, Hossein Abdinasibfar +1
Federated Learning (FL) enables collaborative model training without sharing raw data, making it a promising approach for privacy-sensitive domains. Despite its potential, FL faces…
Split Happens: Combating Advanced Threats with Split Learning and Function Secret Sharing
Tanveer Khan, Mindaugas Budzys, Antonis Michalas
Split Learning (SL) -- splits a model into two distinct parts to help protect client data while enhancing Machine Learning (ML) processes. Though promising, SL has proven vulnerabl…
To Vaccinate or not to Vaccinate? Analyzing Power over the Pandemic
Tanveer Khan, Fahad Sohrab, Antonis Michalas +1
The COVID-19 pandemic has profoundly affected the normal course of life -- from lock-downs and virtual meetings to the unprecedentedly swift creation of vaccines. To halt the COVID…