51 citations · 590 across the 70 of their papers we have counts for
6 papers · 1 filter
Not one but many Tradeoffs: Privacy Vs. Utility in Differentially Private Machine Learning
Benjamin Zi Hao Zhao, Mohamed Ali Kaafar, Nicolas Kourtellis
Data holders are increasingly seeking to protect their user's privacy, whilst still maximizing their ability to produce machine models with high quality predictions. In this work,…
Exploiting Behavioral Side-Channels in Observation Resilient Cognitive Authentication Schemes
Benjamin Zi Hao Zhao, Hassan Jameel Asghar, Mohamed Ali Kaafar +2
Observation Resilient Authentication Schemes (ORAS) are a class of shared secret challenge-response identification schemes where a user mentally computes the response via a cogniti…
Unsupervised Learning for security of Enterprise networks by micro-segmentation
Mahmood Yousefi-Azar, Mohamed-Ali Kaafar, Andy Walker
Micro-segmentation is a network security technique that requires delivering services for each unique segment. To do so, the first stage is defining these unique segments (a.k.a sec…
The Cost of Privacy in Asynchronous Differentially-Private Machine Learning
Farhad Farokhi, Nan Wu, David Smith +1
We consider training machine learning models using Training data located on multiple private and geographically-scattered servers with different privacy settings. Due to the distri…
On the Resilience of Biometric Authentication Systems against Random Inputs
Benjamin Zi Hao Zhao, Hassan Jameel Asghar, Mohamed Ali Kaafar
We assess the security of machine learning based biometric authentication systems against an attacker who submits uniform random inputs, either as feature vectors or raw inputs, in…
Modelling and Quantifying Membership Information Leakage in Machine Learning
Farhad Farokhi, Mohamed Ali Kaafar
Machine learning models have been shown to be vulnerable to membership inference attacks, i.e., inferring whether individuals' data have been used for training models. The lack of…