1 code implementation • 2 Jul 2018 • Sakshi Udeshi, Pryanshu Arora, Sudipta Chattopadhyay
We show that AEQUITAS effectively generates inputs to uncover fairness violation in all the subject classifiers and systematically improves the fairness of the respective models using the generated test inputs.
2 code implementations • 16 Jul 2018 • Guanhua Wang, Sudipta Chattopadhyay, Ivan Gotovchits, Tulika Mitra, Abhik Roychoudhury
In this paper, we propose oo7, a static analysis approach that can mitigate Spectre attacks by detecting potentially vulnerable code snippets in program binaries and protecting them against the attack by patching them.
Cryptography and Security
1 code implementation • 26 Feb 2019 • Sakshi Udeshi, Sudipta Chattopadhyay
The massive progress of machine learning has seen its application over a variety of domains in the past decade.
no code implementations • 2 Aug 2019 • Jingxuan Jiang, Chundong Wang, Sudipta Chattopadhyay, Wei zhang
With such ongoing road context, RAIDS validates corresponding frames observed on the in-vehicle network.
2 code implementations • 6 Aug 2019 • Sakshi Udeshi, Shanshan Peng, Gerald Woo, Lionell Loh, Louth Rawshan, Sudipta Chattopadhyay
In this work, we present NEO, a model agnostic framework to detect and mitigate such backdoor attacks in image classification ML models.
1 code implementation • 2 Sep 2019 • Guanhua Wang, Sudipta Chattopadhyay, Arnab Kumar Biswas, Tulika Mitra, Abhik Roychoudhury
Spectre attacks disclosed in early 2018 expose data leakage scenarios via cache side channels.
Cryptography and Security
no code implementations • 11 Dec 2019 • Sakshi Udeshi, Xingbin Jiang, Sudipta Chattopadhyay
We conduct and present an extensive user study to validate the results of CALLISTO on identifying low quality data from four state-of-the-art real world datasets.
1 code implementation • 25 Feb 2020 • Ezekiel Soremekun, Sakshi Udeshi, Sudipta Chattopadhyay
Specifically, given a robust Deep Neural Network (DNN) that is trained using PGD-based first-order adversarial training approach, AEGIS uses feature clustering to effectively detect whether such DNNs are backdoor-infected or clean.
1 code implementation • 6 Oct 2020 • Ezekiel Soremekun, Sakshi Udeshi, Sudipta Chattopadhyay
We propose a grammar-based fairness testing approach (called ASTRAEA) which leverages context-free grammars to generate discriminatory inputs that reveal fairness violations in software systems.
no code implementations • 23 Dec 2020 • Eyasu Getahun Chekole, Martin Ochoa, Sudipta Chattopadhyay
We empirically measure the computational overhead caused by our approach on two experimental settings based on real CPS.
Cryptography and Security
no code implementations • 22 May 2021 • Yifan Jia, Jingyi Wang, Christopher M. Poskitt, Sudipta Chattopadhyay, Jun Sun, Yuqi Chen
The threats faced by cyber-physical systems (CPSs) in critical infrastructure have motivated research into a multitude of attack detection mechanisms, including anomaly detectors based on neural network models.
1 code implementation • 19 Oct 2021 • Sai Sathiesh Rajan, Sakshi Udeshi, Sudipta Chattopadhyay
AequeVox simulates different environments to assess the effectiveness of ASR systems for different populations.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +3
no code implementations • 29 Dec 2021 • Guoliang Dong, Jingyi Wang, Jun Sun, Sudipta Chattopadhyay, Xinyu Wang, Ting Dai, Jie Shi, Jin Song Dong
Furthermore, such attacks are impossible to eliminate, i. e., the adversarial perturbation is still possible after applying mitigation methods such as adversarial training.
no code implementations • 8 May 2023 • Sai Sathiesh Rajan, Ezekiel Soremekun, Yves Le Traon, Sudipta Chattopadhyay
This work addresses how to validate group fairness in image recognition software.
no code implementations • 19 May 2023 • Sudipta Chattopadhyay, Srikant Sukumar, Vivek Natarajan
The unknown parameter can be reconstructed using the transfer function coefficient estimates obtained with n large and the algebraic expressions relating the transfer function coefficients to the unknown parameter.
no code implementations • 23 Aug 2023 • Sudipta Chattopadhyay, Srikant Sukumar, Vivek Natarajan
Several modifications of the model reference adaptive control (MRAC) framework have been proposed to address input constraints in uncertain linear systems.