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07/11/2023
FairLay-ML: Intuitive Remedies for Unfairness in Data-Driven Social-Critical Algorithms
This thesis explores open-sourced machine learning (ML) model explanatio...
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04/09/2023
Information-Theoretic Testing and Debugging of Fairness Defects in Deep Neural Networks
The deep feedforward neural networks (DNNs) are increasingly deployed in...
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05/10/2022
Metamorphic Testing and Debugging of Tax Preparation Software
This paper presents a data-driven debugging framework to improve the tru...
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06/07/2021
QFuzz: Quantitative Fuzzing for Side Channels
Side channels pose a significant threat to the confidentiality of softwa...
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06/03/2020
Detecting and Understanding Real-World Differential Performance Bugs in Machine Learning Libraries
Programming errors that degrade the performance of systems are widesprea...
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07/23/2019
Efficient Detection and Quantification of Timing Leaks with Neural Networks
Detection and quantification of information leaks through timing side ch...
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06/21/2019
Quantitative Mitigation of Timing Side Channels
Timing side channels pose a significant threat to the security and priva...
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08/30/2018
Data-Driven Debugging for Functional Side Channels
Functional side channels arise when an attacker knows that the secret va...
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11/11/2017
