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09/20/2023
It's Simplex! Disaggregating Measures to Improve Certified Robustness
Certified robustness circumvents the fragility of defences against adver...
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08/15/2023
Enhancing the Antidote: Improved Pointwise Certifications against Poisoning Attacks
Poisoning attacks can disproportionately influence model behaviour by ma...
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02/09/2023
Exploiting Certified Defences to Attack Randomised Smoothing
In guaranteeing that no adversarial examples exist within a bounded regi...
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01/31/2023
Certified Robustness of Learning-based Static Malware Detectors
Certified defenses are a recent development in adversarial machine learn...
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01/08/2023
Bayesian Graphical Entity Resolution Using Exchangeable Random Partition Priors
Entity resolution (record linkage or deduplication) is the process of id...
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10/12/2022
Double Bubble, Toil and Trouble: Enhancing Certified Robustness through Transitivity
In response to subtle adversarial examples flipping classifications of n...
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10/11/2022
Unlabelled Sample Compression Schemes for Intersection-Closed Classes and Extremal Classes
The sample compressibility of concept classes plays an important role in...
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07/23/2022
Testing the Robustness of Learned Index Structures
While early empirical evidence has supported the case for learned index ...
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05/20/2022
Getting a-Round Guarantees: Floating-Point Attacks on Certified Robustness
Adversarial examples pose a security risk as they can alter a classifier...
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12/24/2021
State Selection Algorithms and Their Impact on The Performance of Stateful Network Protocol Fuzzing
The statefulness property of network protocol implementations poses a un...
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12/10/2021
Are We There Yet? Timing and Floating-Point Attacks on Differential Privacy Systems
Differential privacy is a de facto privacy framework that has seen adopt...
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09/29/2021
A Communication Security Game on Switched Systems for Autonomous Vehicle Platoons
Vehicle-to-vehicle communication enables autonomous platoons to boost tr...
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09/24/2021
Local Intrinsic Dimensionality Signals Adversarial Perturbations
The vulnerability of machine learning models to adversarial perturbation...
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09/17/2021
Hard to Forget: Poisoning Attacks on Certified Machine Unlearning
The right to erasure requires removal of a user's information from data ...
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08/23/2021
No DBA? No regret! Multi-armed bandits for index tuning of analytical and HTAP workloads with provable guarantees
Automating physical database design has remained a long-term interest in...
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07/18/2021
As Easy as 1, 2, 3: Behavioural Testing of NMT Systems for Numerical Translation
Mistranslated numbers have the potential to cause serious effects, such ...
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07/12/2021
Putting words into the system's mouth: A targeted attack on neural machine translation using monolingual data poisoning
Neural machine translation systems are known to be vulnerable to adversa...
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11/04/2020
Not fit for Purpose: A critical analysis of the 'Five Safes'
Adopted by government agencies in Australia, New Zealand and the UK as p...
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11/02/2020
Targeted Poisoning Attacks on Black-Box Neural Machine Translation
As modern neural machine translation (NMT) systems have been widely depl...
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10/19/2020
DBA bandits: Self-driving index tuning under ad-hoc, analytical workloads with safety guarantees
Automating physical database design has remained a long-term interest in...
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07/12/2020
A Graph Symmetrisation Bound on Channel Information Leakage under Blowfish Privacy
Blowfish privacy is a recent generalisation of differential privacy that...
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06/23/2020
Discrete Few-Shot Learning for Pan Privacy
In this paper we present the first baseline results for the task of few-...
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06/12/2020
A general framework for label-efficient online evaluation with asymptotic guarantees
Achieving statistically significant evaluation with passive sampling of ...
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05/28/2020
Assessing Centrality Without Knowing Connections
We consider the privacy-preserving computation of node influence in dist...
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02/15/2020
Legion: Best-First Concolic Testing
Legion is a grey-box concolic tool that aims to balance the complementar...
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09/13/2019
d-blink: Distributed End-to-End Bayesian Entity Resolution
Entity resolution (ER) (record linkage or de-duplication) is the process...
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02/25/2019
Adversarial Reinforcement Learning under Partial Observability in Software-Defined Networking
Recent studies have demonstrated that reinforcement learning (RL) agents...
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02/24/2019
Truth Inference at Scale: A Bayesian Model for Adjudicating Highly Redundant Crowd Annotations
Crowd-sourcing is a cheap and popular means of creating training and eva...
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02/20/2019
A Note on Bounding Regret of the C^2UCB Contextual Combinatorial Bandit
We revisit the proof by Qin et al. (2014) of bounded regret of the C^2UC...
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01/16/2019
Differentially-Private Two-Party Egocentric Betweenness Centrality
We describe a novel protocol for computing the egocentric betweenness ce...
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08/17/2018
Reinforcement Learning for Autonomous Defence in Software-Defined Networking
Despite the successful application of machine learning (ML) in a wide ra...
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02/22/2018
Options for encoding names for data linking at the Australian Bureau of Statistics
Publicly, ABS has said it would use a cryptographic hash function to con...
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12/15/2017
Health Data in an Open World
With the aim of informing sound policy about data sharing and privacy, w...
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12/04/2017
Vulnerabilities in the use of similarity tables in combination with pseudonymisation to preserve data privacy in the UK Office for National Statistics' Privacy-Preserving Recor
In the course of a survey of privacy-preserving record linkage, we revie...
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06/08/2017
Pain-Free Random Differential Privacy with Sensitivity Sampling
Popular approaches to differential privacy, such as the Laplace and expo...
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04/06/2017
Adequacy of the Gradient-Descent Method for Classifier Evasion Attacks
Despite the wide use of machine learning in adversarial settings includi...
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03/02/2017
In Search of an Entity Resolution OASIS: Optimal Asymptotic Sequential Importance Sampling
Entity resolution (ER) presents unique challenges for evaluation methodo...
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07/29/2016
TopicResponse: A Marriage of Topic Modelling and Rasch Modelling for Automatic Measurement in MOOCs
This paper explores the suitability of using automatically discovered to...
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02/03/2014
Principled Graph Matching Algorithms for Integrating Multiple Data Sources
This paper explores combinatorial optimization for problems of max-weigh...
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01/29/2014
Bounding Embeddings of VC Classes into Maximum Classes
One of the earliest conjectures in computational learning theory-the Sam...
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11/18/2009