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06/02/2023
Hyperparameter Learning under Data Poisoning: Analysis of the Influence of Regularization via Multiobjective Bilevel Optimization
Machine Learning (ML) algorithms are vulnerable to poisoning attacks, wh...
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12/02/2021
FedRAD: Federated Robust Adaptive Distillation
The robustness of federated learning (FL) is vital for the distributed t...
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05/23/2021
Regularization Can Help Mitigate Poisoning Attacks... with the Right Hyperparameters
Machine learning algorithms are vulnerable to poisoning attacks, where a...
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05/16/2021
Real-time Detection of Practical Universal Adversarial Perturbations
Universal Adversarial Perturbations (UAPs) are a prominent class of adve...
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02/12/2021
Universal Adversarial Perturbations for Malware
Machine learning classification models are vulnerable to adversarial exa...
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12/10/2020
Robustness and Transferability of Universal Attacks on Compressed Models
Neural network compression methods like pruning and quantization are ver...
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09/17/2020
Robust Aggregation for Adaptive Privacy Preserving Federated Learning in Healthcare
Federated learning (FL) has enabled training models collaboratively from...
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08/27/2020
GhostBuster: Looking Into Shadows to Detect Ghost Objects in Autonomous Vehicle 3D Sensing
LiDAR-driven 3D sensing allows new generations of vehicles to achieve ad...
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02/28/2020
Regularisation Can Mitigate Poisoning Attacks: A Novel Analysis Based on Multiobjective Bilevel Optimisation
Machine Learning (ML) algorithms are vulnerable to poisoning attacks, wh...
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11/23/2019
Universal Adversarial Perturbations to Understand Robustness of Texture vs. Shape-biased Training
Convolutional Neural Networks (CNNs) used on image classification tasks ...
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09/11/2019
Byzantine-Robust Federated Machine Learning through Adaptive Model Averaging
Federated learning enables training collaborative machine learning model...
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06/18/2019
Poisoning Attacks with Generative Adversarial Nets
Machine learning algorithms are vulnerable to poisoning attacks: An adve...
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06/08/2019
Sensitivity of Deep Convolutional Networks to Gabor Noise
Deep Convolutional Networks (DCNs) have been shown to be sensitive to Un...
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04/05/2019
Efficient attack countermeasure selection accounting for recovery and action costs
The losses arising from a system being hit by cyber attacks can be stagg...
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09/30/2018
Procedural Noise Adversarial Examples for Black-Box Attacks on Deep Neural Networks
Deep neural networks have been shown to be vulnerable to adversarial exa...
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08/16/2018
Mitigation of Adversarial Attacks through Embedded Feature Selection
Machine learning has become one of the main components for task automati...
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04/20/2018
Approaches to Enhancing Cyber Resilience: Report of the North Atlantic Treaty Organization (NATO) Workshop IST-153
This report summarizes the discussions and findings of the 2017 North At...
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03/02/2018
Label Sanitization against Label Flipping Poisoning Attacks
Many machine learning systems rely on data collected in the wild from un...
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02/08/2018
Detection of Adversarial Training Examples in Poisoning Attacks through Anomaly Detection
Machine learning has become an important component for many systems and ...
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06/22/2016
Efficient Attack Graph Analysis through Approximate Inference
Attack graphs provide compact representations of the attack paths that a...
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10/08/2015