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08/03/2023
URET: Universal Robustness Evaluation Toolkit (for Evasion)
Machine learning models are known to be vulnerable to adversarial evasio...
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10/25/2022
Accelerating Certified Robustness Training via Knowledge Transfer
Training deep neural network classifiers that are certifiably robust aga...
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10/24/2022
Ares: A System-Oriented Wargame Framework for Adversarial ML
Since the discovery of adversarial attacks against machine learning mode...
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02/21/2022
Transferring Adversarial Robustness Through Robust Representation Matching
With the widespread use of machine learning, concerns over its security ...
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05/19/2021
Separation of Powers in Federated Learning
Federated Learning (FL) enables collaborative training among mutually di...
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12/14/2020
Adaptive Verifiable Training Using Pairwise Class Similarity
Verifiable training has shown success in creating neural networks that a...
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11/27/2019
Can Attention Masks Improve Adversarial Robustness?
Deep Neural Networks (DNNs) are known to be susceptible to adversarial e...
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09/12/2019
Transferable Adversarial Robustness using Adversarially Trained Autoencoders
Machine learning has proven to be an extremely useful tool for solving c...
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05/26/2019
Robust Classification using Robust Feature Augmentation
Existing deep neural networks, say for image classification, have been s...
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12/17/2018
Designing Adversarially Resilient Classifiers using Resilient Feature Engineering
We provide a methodology, resilient feature engineering, for creating ad...
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07/20/2018
Physical Adversarial Examples for Object Detectors
Deep neural networks (DNNs) are vulnerable to adversarial examples-malic...
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01/14/2018
Tyche: Risk-Based Permissions for Smart Home Platforms
Emerging smart home platforms, which interface with a variety of physica...
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12/21/2017
