Publications (16)
Verified Foundations for Differential Privacy
Markus de Medeiros, Muhammad Naveed, Tancrède Lepoint +7
Differential privacy (DP) has become the gold standard for privacy-preserving data analysis, but implementing it correctly has proven challenging. Prior work has focused on verifyi…
V-SenseDrive: A Privacy-Preserving Road Video and In-Vehicle Sensor Fusion Framework for Road Safety & Driver Behaviour Modelling
Muhammad Naveed, Nazia Perwaiz, Sidra Sultana +2
Road traffic accidents remain a major public health challenge, particularly in countries with heterogeneous road conditions, mixed traffic flow, and variable driving discipline, su…
Characterizing Improper Input Validation Vulnerabilities of Mobile Crowdsourcing Services
Sojhal Ismail Khan, Dominika Woszczyk, Chengzeng You +2
Mobile crowdsourcing services (MCS), enable fast and economical data acquisition at scale and find applications in a variety of domains. Prior work has shown that Foursquare and Wa…
Non-topological Origin of the Planar Hall Effect in Type-II Dirac Semimetal NiTe2
Qianqian Liu, Bo Chen, Boyuan Wei +7
Dirac and Weyl semimetals are new discovered topological nontrivial materials with the linear band dispersions around the Dirac/Weyl points. When applying non-orthogonal electric c…
Hawk: Accurate and Fast Privacy-Preserving Machine Learning Using Secure Lookup Table Computation
Hamza Saleem, Amir Ziashahabi, Muhammad Naveed +1
Training machine learning models on data from multiple entities without direct data sharing can unlock applications otherwise hindered by business, legal, or ethical constraints. I…
Secure Neuroimaging Analysis using Federated Learning with Homomorphic Encryption
Dimitris Stripelis, Hamza Saleem, Tanmay Ghai +8
Federated learning (FL) enables distributed computation of machine learning models over various disparate, remote data sources, without requiring to transfer any individual data to…