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12/12/2022
A Survey on Reinforcement Learning Security with Application to Autonomous Driving
Reinforcement learning allows machines to learn from their own experienc...
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11/05/2022
Stateful Detection of Adversarial Reprogramming
Adversarial reprogramming allows stealing computational resources by rep...
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08/10/2022
Explaining Machine Learning DGA Detectors from DNS Traffic Data
One of the most common causes of lack of continuity of online systems st...
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08/09/2022
Robust Machine Learning for Malware Detection over Time
The presence and persistence of Android malware is an on-going threat th...
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03/07/2022
ImageNet-Patch: A Dataset for Benchmarking Machine Learning Robustness against Adversarial Patches
Adversarial patches are optimized contiguous pixel blocks in an input im...
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11/22/2021
Evaluating Adversarial Attacks on ImageNet: A Reality Check on Misclassification Classes
Although ImageNet was initially proposed as a dataset for performance be...
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08/26/2021
Why Adversarial Reprogramming Works, When It Fails, and How to Tell the Difference
Adversarial reprogramming allows repurposing a machine-learning model to...
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06/18/2021
Indicators of Attack Failure: Debugging and Improving Optimization of Adversarial Examples
Evaluating robustness of machine-learning models to adversarial examples...
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02/25/2021
Fast Minimum-norm Adversarial Attacks through Adaptive Norm Constraints
Evaluating adversarial robustness amounts to finding the minimum perturb...
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10/13/2020
Detecting Anomalies from Video-Sequences: a Novel Descriptor
We present a novel descriptor for crowd behavior analysis and anomaly de...
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12/20/2019
secml: A Python Library for Secure and Explainable Machine Learning
We present secml, an open-source Python library for secure and explainab...
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09/08/2018