51 citations · 348 across the 61 of their papers we have counts for
7 papers · 1 filter
Are We There Yet? Timing and Floating-Point Attacks on Differential Privacy Systems
Jiankai Jin, Eleanor McMurtry, Benjamin I. P. Rubinstein +1
Differential privacy is a de facto privacy framework that has seen adoption in practice via a number of mature software platforms. Implementation of differentially private (DP) mec…
Local Intrinsic Dimensionality Signals Adversarial Perturbations
Sandamal Weerasinghe, Tansu Alpcan, Sarah M. Erfani +2
The vulnerability of machine learning models to adversarial perturbations has motivated a significant amount of research under the broad umbrella of adversarial machine learning. S…
Hard to Forget: Poisoning Attacks on Certified Machine Unlearning
Neil G. Marchant, Benjamin I. P. Rubinstein, Scott Alfeld
The right to erasure requires removal of a user's information from data held by organizations, with rigorous interpretations extending to downstream products such as learned models…
No DBA? No regret! Multi-armed bandits for index tuning of analytical and HTAP workloads with provable guarantees
R. Malinga Perera, Bastian Oetomo, Benjamin I. P. Rubinstein +1
Automating physical database design has remained a long-term interest in database research due to substantial performance gains afforded by optimised structures. Despite significan…
As Easy as 1, 2, 3: Behavioural Testing of NMT Systems for Numerical Translation
Jun Wang, Chang Xu, Francisco Guzman +3
Mistranslated numbers have the potential to cause serious effects, such as financial loss or medical misinformation. In this work we develop comprehensive assessments of the robust…
Putting words into the system's mouth: A targeted attack on neural machine translation using monolingual data poisoning
Jun Wang, Chang Xu, Francisco Guzman +4
Neural machine translation systems are known to be vulnerable to adversarial test inputs, however, as we show in this paper, these systems are also vulnerable to training attacks.…
TRS: Transferability Reduced Ensemble via Encouraging Gradient Diversity and Model Smoothness
Zhuolin Yang, Linyi Li, Xiaojun Xu +6
Adversarial Transferability is an intriguing property - adversarial perturbation crafted against one model is also effective against another model, while these models are from diff…