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02/06/2023
Closed-loop Analysis of Vision-based Autonomous Systems: A Case Study
Deep neural networks (DNNs) are increasingly used in safety-critical aut...
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08/05/2022
An Overview of Structural Coverage Metrics for Testing Neural Networks
Deep neural network (DNN) models, including those used in safety-critica...
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05/08/2022
VPN: Verification of Poisoning in Neural Networks
Neural networks are successfully used in a variety of applications, many...
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01/31/2022
AntidoteRT: Run-time Detection and Correction of Poison Attacks on Neural Networks
We study backdoor poisoning attacks against image classification network...
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10/25/2021
QuantifyML: How Good is my Machine Learning Model?
The efficacy of machine learning models is typically determined by compu...
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03/02/2021
DeepCert: Verification of Contextually Relevant Robustness for Neural Network Image Classifiers
We introduce DeepCert, a tool-supported method for verifying the robustn...
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04/29/2019
Finding Invariants in Deep Neural Networks
We present techniques for automatically inferring invariant properties o...
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11/16/2018
DifFuzz: Differential Fuzzing for Side-Channel Analysis
Side-channel attacks allow an adversary to uncover secret program data b...
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10/18/2018
Compositional Verification for Autonomous Systems with Deep Learning Components
As autonomy becomes prevalent in many applications, ranging from recomme...
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07/27/2018
Symbolic Execution for Deep Neural Networks
Deep Neural Networks (DNN) are increasingly used in a variety of applica...
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06/08/2018
Badger: Complexity Analysis with Fuzzing and Symbolic Execution
Hybrid testing approaches that involve fuzz testing and symbolic executi...
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10/02/2017
