Somesh Jha

ORCID

Publication Activity (10 Years)

Years Active: 1992-2024
Publications (10 Years): 190

Top Venues

Publications

Ashish Hooda, Mihai Christodorescu, Miltos Allamanis, Aaron Wilson, Kassem Fawaz, Somesh Jha
Do Large Code Models Understand Programming Concepts? A Black-box Approach. CoRR (2024)
Mingtian Tan, Tianhao Wang, Somesh Jha
A Somewhat Robust Image Watermark against Diffusion-based Editing Models. CoRR (2023)
Ryan Feng, Ashish Hooda, Neal Mangaokar, Kassem Fawaz, Somesh Jha, Atul Prakash
Stateful Defenses for Machine Learning Models Are Not Yet Secure Against Black-box Attacks. CCS (2023)
Olive Franzese, Adam Dziedzic, Christopher A. Choquette-Choo, Mark R. Thomas, Muhammad Ahmad Kaleem, Stephan Rabanser, Congyu Fang, Somesh Jha, Nicolas Papernot, Xiao Wang
Robust and Actively Secure Serverless Collaborative Learning. CoRR (2023)
Xi Wu, Xiangyao Yu, Shaleen Deep, Ahmed Mahmood, Uyeong Jang, Stratis Viglas, Somesh Jha, John Cieslewicz, Jeffrey F. Naughton
Bilevel Relations and Their Applications to Data Insights. CoRR (2023)
Joann Qiongna Chen, Tianhao Wang, Zhikun Zhang, Yang Zhang, Somesh Jha, Zhou Li
Differentially Private Resource Allocation. ACSAC (2023)
Xi Wu, Joe Benassi, Yaqi Zhang, Uyeong Jang, James Foster, Stella Kim, Yujing Sun, Somesh Jha, John Cieslewicz, Jeffrey F. Naughton
Holistic Cube Analysis: A Query Framework for Data Insights. CoRR (2023)
Zhenmei Shi, Jiefeng Chen, Kunyang Li, Jayaram Raghuram, Xi Wu, Yingyu Liang, Somesh Jha
The Trade-off between Universality and Label Efficiency of Representations from Contrastive Learning. ICLR (2023)
Jaiden Fairoze, Sanjam Garg, Somesh Jha, Saeed Mahloujifar, Mohammad Mahmoody, Mingyuan Wang
Publicly Detectable Watermarking for Language Models. CoRR (2023)
Jiefeng Chen, Jinsung Yoon, Sayna Ebrahimi, Sercan Ö. Arik, Tomas Pfister, Somesh Jha
Adaptation with Self-Evaluation to Improve Selective Prediction in LLMs. CoRR (2023)
Clark W. Barrett, Brad Boyd, Ellie Burzstein, Nicholas Carlini, Brad Chen, Jihye Choi, Amrita Roy Chowdhury, Mihai Christodorescu, Anupam Datta, Soheil Feizi, Kathleen Fisher, Tatsunori Hashimoto, Dan Hendrycks, Somesh Jha, Daniel Kang, Florian Kerschbaum, Eric Mitchell, John C. Mitchell, Zulfikar Ramzan, Khawaja Shams, Dawn Song, Ankur Taly, Diyi Yang
Identifying and Mitigating the Security Risks of Generative AI. CoRR (2023)
Zi Wang, Jihye Choi, Somesh Jha
Rethink Diversity in Deep Learning Testing. CoRR (2023)
Nicholas Franzese, Adam Dziedzic, Christopher A. Choquette-Choo, Mark R. Thomas, Muhammad Ahmad Kaleem, Stephan Rabanser, Congyu Fang, Somesh Jha, Nicolas Papernot, Xiao Wang
Robust and Actively Secure Serverless Collaborative Learning. NeurIPS (2023)
Harrison Rosenberg, Brian Tang, Kassem Fawaz, Somesh Jha
Fairness Properties of Face Recognition and Obfuscation Systems. USENIX Security Symposium (2023)
Jiefeng Chen, Jayaram Raghuram, Jihye Choi, Xi Wu, Yingyu Liang, Somesh Jha
Stratified Adversarial Robustness with Rejection. CoRR (2023)
Zhenmei Shi, Jiefeng Chen, Kunyang Li, Jayaram Raghuram, Xi Wu, Yingyu Liang, Somesh Jha
The Trade-off between Universality and Label Efficiency of Representations from Contrastive Learning. CoRR (2023)
Adam Dziedzic, Christopher A. Choquette-Choo, Natalie Dullerud, Vinith M. Suriyakumar, Ali Shahin Shamsabadi, Muhammad Ahmad Kaleem, Somesh Jha, Nicolas Papernot, Xiao Wang
Private Multi-Winner Voting for Machine Learning. Proc. Priv. Enhancing Technol. 2023 (1) (2023)
Mohannad Alhanahnah, Shiqing Ma, Ashish Gehani, Gabriela F. Ciocarlie, Vinod Yegneswaran, Somesh Jha, Xiangyu Zhang
autoMPI: Automated Multiple Perspective Attack Investigation With Semantics Aware Execution Partitioning. IEEE Trans. Software Eng. 49 (4) (2023)
Ryan Feng, Ashish Hooda, Neal Mangaokar, Kassem Fawaz, Somesh Jha, Atul Prakash
Investigating Stateful Defenses Against Black-Box Adversarial Examples. CoRR (2023)
Samarjit Chakraborty, Somesh Jha, Soheil Samii, Philipp Mundhenk
Introduction to the Special Issue on Automotive CPS Safety & Security: Part 1. ACM Trans. Cyber Phys. Syst. 7 (1) (2023)
Zhichuang Sun, Ruimin Sun, Changming Liu, Amrita Roy Chowdhury, Long Lu, Somesh Jha
ShadowNet: A Secure and Efficient On-device Model Inference System for Convolutional Neural Networks. SP (2023)
Debopam Sanyal, Jui-Tse Hung, Manav Agrawal, Prahlad Jasti, Shahab Nikkhoo, Somesh Jha, Tianhao Wang, Sibin Mohan, Alexey Tumanov
Pareto-Secure Machine Learning (PSML): Fingerprinting and Securing Inference Serving Systems. CoRR (2023)
Clark W. Barrett, Brad Boyd, Elie Bursztein, Nicholas Carlini, Brad Chen, Jihye Choi, Amrita Roy Chowdhury, Mihai Christodorescu, Anupam Datta, Soheil Feizi, Kathleen Fisher, Tatsunori Hashimoto, Dan Hendrycks, Somesh Jha, Daniel Kang, Florian Kerschbaum, Eric Mitchell, John C. Mitchell, Zulfikar Ramzan, Khawaja Shams, Dawn Song, Ankur Taly, Diyi Yang
Identifying and Mitigating the Security Risks of Generative AI. Found. Trends Priv. Secur. 6 (1) (2023)
Somesh Jha, Mihai Christodorescu, Anh Pham
Formal Analysis of the API Proxy Problem. CoRR (2023)
Jiefeng Chen, Jinsung Yoon, Sayna Ebrahimi, Sercan Ö. Arik, Somesh Jha, Tomas Pfister
ASPEST: Bridging the Gap Between Active Learning and Selective Prediction. CoRR (2023)
Ashish Hooda, Neal Mangaokar, Ryan Feng, Kassem Fawaz, Somesh Jha, Atul Prakash
Theoretically Principled Trade-off for Stateful Defenses against Query-Based Black-Box Attacks. CoRR (2023)
Jihye Choi, Shruti Tople, Varun Chandrasekaran, Somesh Jha
Why Train More? Effective and Efficient Membership Inference via Memorization. CoRR (2023)
Mohannad Alhanahnah, Philipp Dominik Schubert, Thomas W. Reps, Somesh Jha, Eric Bodden
slash: A Technique for Static Configuration-Logic Identification. CoRR (2023)
Sanjam Garg, Aarushi Goel, Somesh Jha, Saeed Mahloujifar, Mohammad Mahmoody, Guru-Vamsi Policharla, Mingyuan Wang
Experimenting with Zero-Knowledge Proofs of Training. IACR Cryptol. ePrint Arch. 2023 (2023)
Jaiden Fairoze, Sanjam Garg, Somesh Jha, Saeed Mahloujifar, Mohammad Mahmoody, Mingyuan Wang
Publicly Detectable Watermarking for Language Models. IACR Cryptol. ePrint Arch. 2023 (2023)
Jihye Choi, Jayaram Raghuram, Ryan Feng, Jiefeng Chen, Somesh Jha, Atul Prakash
Concept-based Explanations for Out-of-Distribution Detectors. ICML (2023)
Sanjam Garg, Aarushi Goel, Somesh Jha, Saeed Mahloujifar, Mohammad Mahmoody, Guru-Vamsi Policharla, Mingyuan Wang
Experimenting with Zero-Knowledge Proofs of Training. CCS (2023)
Nils Palumbo, Yang Guo, Xi Wu, Jiefeng Chen, Yingyu Liang, Somesh Jha
Two Heads are Better than One: Towards Better Adversarial Robustness by Combining Transduction and Rejection. CoRR (2023)
Jayaram Raghuram, Yijing Zeng, Dolores García, Rafael Ruiz, Somesh Jha, Joerg Widmer, Suman Banerjee
Few-Shot Domain Adaptation For End-to-End Communication. ICLR (2023)
Matt Fredrikson, Kaiji Lu, Saranya Vijayakumar, Somesh Jha, Vijay Ganesh, Zifan Wang
Learning Modulo Theories. CoRR (2023)
Zifan Wang, Saranya Vijayakumar, Kaiji Lu, Vijay Ganesh, Somesh Jha, Matt Fredrikson
Grounding Neural Inference with Satisfiability Modulo Theories. NeurIPS (2023)
Jiefeng Chen, Jayaram Raghuram, Jihye Choi, Xi Wu, Yingyu Liang, Somesh Jha
Stratified Adversarial Robustness with Rejection. ICML (2023)
Zi Wang, Somesh Jha, Krishnamurthy Dvijotham
Efficient Symbolic Reasoning for Neural-Network Verification. CoRR (2023)
Jiefeng Chen, Jinsung Yoon, Sayna Ebrahimi, Sercan Ö Arik, Tomas Pfister, Somesh Jha
Adaptation with Self-Evaluation to Improve Selective Prediction in LLMs. EMNLP (Findings) (2023)
Saeed Mahloujifar, Alexandre Sablayrolles, Graham Cormode, Somesh Jha
Optimal Membership Inference Bounds for Adaptive Composition of Sampled Gaussian Mechanisms. CoRR (2022)
Ashish Hooda, Neal Mangaokar, Ryan Feng, Kassem Fawaz, Somesh Jha, Atul Prakash
Towards Adversarially Robust Deepfake Detection: An Ensemble Approach. CoRR (2022)
Amrita Roy Chowdhury, Chuan Guo, Somesh Jha, Laurens van der Maaten
EIFFeL: Ensuring Integrity for Federated Learning. CCS (2022)
Yizhen Wang, Mohannad Alhanahnah, Xiaozhu Meng, Ke Wang, Mihai Christodorescu, Somesh Jha
Robust Learning against Relational Adversaries. NeurIPS (2022)
Samuel Maddock, Graham Cormode, Tianhao Wang, Carsten Maple, Somesh Jha
Federated Boosted Decision Trees with Differential Privacy. CCS (2022)
Mohannad Alhanahnah, Rithik Jain, Vaibhav Rastogi, Somesh Jha, Thomas W. Reps
Lightweight, Multi-Stage, Compiler-Assisted Application Specialization. EuroS&P (2022)
Amrita Roy Chowdhury, Bolin Ding, Somesh Jha, Weiran Liu, Jingren Zhou
Strengthening Order Preserving Encryption with Differential Privacy. CCS (2022)
Ryan Feng, Somesh Jha, Atul Prakash
Constraining the Attack Space of Machine Learning Models with Distribution Clamping Preprocessing. CoRR (2022)
Casey Meehan, Amrita Roy Chowdhury, Kamalika Chaudhuri, Somesh Jha
Privacy Implications of Shuffling. ICLR (2022)
Zi Wang, Gautam Prakriya, Somesh Jha
A Quantitative Geometric Approach to Neural-Network Smoothness. NeurIPS (2022)
Zi Wang, Aws Albarghouthi, Gautam Prakriya, Somesh Jha
Interval universal approximation for neural networks. Proc. ACM Program. Lang. 6 (POPL) (2022)
Jihye Choi, Jayaram Raghuram, Ryan Feng, Jiefeng Chen, Somesh Jha, Atul Prakash
Concept-based Explanations for Out-Of-Distribution Detectors. CoRR (2022)
Ryan Feng, Neal Mangaokar, Jiefeng Chen, Earlence Fernandes, Somesh Jha, Atul Prakash
GRAPHITE: Generating Automatic Physical Examples for Machine-Learning Attacks on Computer Vision Systems. EuroS&P (2022)
Sanjam Garg, Somesh Jha, Saeed Mahloujifar, Mohammad Mahmoody, Mingyuan Wang
Overparameterization from Computational Constraints. NeurIPS (2022)
Aiping Xiong, Chuhao Wu, Tianhao Wang, Robert W. Proctor, Jeremiah Blocki, Ninghui Li, Somesh Jha
Using Illustrations to Communicate Differential Privacy Trust Models: An Investigation of Users' Comprehension, Perception, and Data Sharing Decision. CoRR (2022)
Adam Dziedzic, Christopher A. Choquette-Choo, Natalie Dullerud, Vinith Menon Suriyakumar, Ali Shahin Shamsabadi, Muhammad Ahmad Kaleem, Somesh Jha, Nicolas Papernot, Xiao Wang
Private Multi-Winner Voting for Machine Learning. CoRR (2022)
Vijay Ganesh, Sanjit A. Seshia, Somesh Jha
Machine learning and logic: a new frontier in artificial intelligence. Formal Methods Syst. Des. 60 (3) (2022)
Zi Wang, Gautam Prakriya, Somesh Jha
A Quantitative Geometric Approach to Neural Network Smoothness. CoRR (2022)
Samuel Maddock, Graham Cormode, Tianhao Wang, Carsten Maple, Somesh Jha
Federated Boosted Decision Trees with Differential Privacy. CoRR (2022)
Harrison Rosenberg, Robi Bhattacharjee, Kassem Fawaz, Somesh Jha
An Exploration of Multicalibration Uniform Convergence Bounds. CoRR (2022)
Sanjam Garg, Somesh Jha, Saeed Mahloujifar, Mohammad Mahmoody, Mingyuan Wang
Overparameterized (robust) models from computational constraints. CoRR (2022)
Sébastien Bardin, Somesh Jha, Vijay Ganesh
Machine Learning and Logical Reasoning: The New Frontier (Dagstuhl Seminar 22291). Dagstuhl Reports 12 (7) (2022)
Jordan Henkel, Goutham Ramakrishnan, Zi Wang, Aws Albarghouthi, Somesh Jha, Thomas W. Reps
Semantic Robustness of Models of Source Code. SANER (2022)
Jiefeng Chen, Xi Wu, Yang Guo, Yingyu Liang, Somesh Jha
Towards Evaluating the Robustness of Neural Networks Learned by Transduction. ICLR (2022)
Samuel Deng, Sanjam Garg, Somesh Jha, Saeed Mahloujifar, Mohammad Mahmoody, Abhradeep Guha Thakurta
A Separation Result Between Data-oblivious and Data-aware Poisoning Attacks. NeurIPS (2021)
Amrita Roy Chowdhury, Chuan Guo, Somesh Jha, Laurens van der Maaten
EIFFeL: Ensuring Integrity for Federated Learning. CoRR (2021)
Christopher A. Choquette-Choo, Natalie Dullerud, Adam Dziedzic, Yunxiang Zhang, Somesh Jha, Nicolas Papernot, Xiao Wang
CaPC Learning: Confidential and Private Collaborative Learning. CoRR (2021)
Somesh Jha
Trustworthy Machine Learning: Past, Present, and Future. AsiaCCS (2021)
Washington Garcia, Animesh Chhotaray, Joseph I. Choi, Suman Kalyan Adari, Kevin R. B. Butler, Somesh Jha
Brittle Features of Device Authentication. CODASPY (2021)
Hassaan Irshad, Gabriela F. Ciocarlie, Ashish Gehani, Vinod Yegneswaran, Kyu Hyung Lee, Jignesh M. Patel, Somesh Jha, Yonghwi Kwon, Dongyan Xu, Xiangyu Zhang
TRACE: Enterprise-Wide Provenance Tracking for Real-Time APT Detection. IEEE Trans. Inf. Forensics Secur. 16 (2021)
Mohannad Alhanahnah, Rithik Jain, Vaibhav Rastogi, Somesh Jha, Thomas W. Reps
Lightweight, Multi-Stage, Compiler-Assisted Application Specialization. CoRR (2021)
Washington Garcia, Pin-Yu Chen, Somesh Jha, Scott Clouse, Kevin R. B. Butler
Hard-label Manifolds: Unexpected Advantages of Query Efficiency for Finding On-manifold Adversarial Examples. CoRR (2021)
Tianhao Wang, Joann Qiongna Chen, Zhikun Zhang, Dong Su, Yueqiang Cheng, Zhou Li, Ninghui Li, Somesh Jha
Continuous Release of Data Streams under both Centralized and Local Differential Privacy. CCS (2021)
Jiefeng Chen, Xi Wu, Yang Guo, Yingyu Liang, Somesh Jha
Towards Evaluating the Robustness of Neural Networks Learned by Transduction. CoRR (2021)
Nicholas Carlini, Sanjam Garg, Somesh Jha, Saeed Mahloujifar, Mohammad Mahmoody, Florian Tramèr
NeuraCrypt is not private. CoRR (2021)
Harrison Rosenberg, Brian Tang, Kassem Fawaz, Somesh Jha
Fairness Properties of Face Recognition and Obfuscation Systems. CoRR (2021)
Christopher A. Choquette-Choo, Natalie Dullerud, Adam Dziedzic, Yunxiang Zhang, Somesh Jha, Nicolas Papernot, Xiao Wang
CaPC Learning: Confidential and Private Collaborative Learning. ICLR (2021)
Jiefeng Chen, Frederick Liu, Besim Avci, Xi Wu, Yingyu Liang, Somesh Jha
Detecting Errors and Estimating Accuracy on Unlabeled Data with Self-training Ensembles. CoRR (2021)
Tianhao Wang, Ninghui Li, Somesh Jha
Locally Differentially Private Heavy Hitter Identification. IEEE Trans. Dependable Secur. Comput. 18 (2) (2021)
Jiefeng Chen, Yang Guo, Xi Wu, Tianqi Li, Qicheng Lao, Yingyu Liang, Somesh Jha
Towards Adversarial Robustness via Transductive Learning. CoRR (2021)
Jiefeng Chen, Yixuan Li, Xi Wu, Yingyu Liang, Somesh Jha
ATOM: Robustifying Out-of-Distribution Detection Using Outlier Mining. ECML/PKDD (3) (2021)
Jiefeng Chen, Frederick Liu, Besim Avci, Xi Wu, Yingyu Liang, Somesh Jha
Detecting Errors and Estimating Accuracy on Unlabeled Data with Self-training Ensembles. NeurIPS (2021)
Robi Bhattacharjee, Somesh Jha, Kamalika Chaudhuri
Sample Complexity of Robust Linear Classification on Separated Data. ICML (2021)
Nicholas Carlini, Samuel Deng, Sanjam Garg, Somesh Jha, Saeed Mahloujifar, Mohammad Mahmoody, Abhradeep Thakurta, Florian Tramèr
Is Private Learning Possible with Instance Encoding? IEEE Symposium on Security and Privacy (2021)
Thomas Kobber Panum, Zi Wang, Pengyu Kan, Earlence Fernandes, Somesh Jha
Exploring Adversarial Robustness of Deep Metric Learning. CoRR (2021)
Casey Meehan, Amrita Roy Chowdhury, Kamalika Chaudhuri, Somesh Jha
A Shuffling Framework for Local Differential Privacy. CoRR (2021)
Varun Chandrasekaran, Chuhan Gao, Brian Tang, Kassem Fawaz, Somesh Jha, Suman Banerjee
Face-Off: Adversarial Face Obfuscation. Proc. Priv. Enhancing Technol. 2021 (2) (2021)
Kim G. Larsen, Natarajan Shankar, Pierre Wolper, Somesh Jha
2018 CAV award. Formal Methods Syst. Des. 57 (1) (2021)
Jayaram Raghuram, Yijing Zeng, Dolores García Martí, Somesh Jha, Suman Banerjee, Joerg Widmer, Rafael Ruiz Ortiz
Domain Adaptation for Autoencoder-Based End-to-End Communication Over Wireless Channels. CoRR (2021)
Varun Chandrasekaran, Darren Edge, Somesh Jha, Amit Sharma, Cheng Zhang, Shruti Tople
Causally Constrained Data Synthesis for Private Data Release. CoRR (2021)
Jayaram Raghuram, Varun Chandrasekaran, Somesh Jha, Suman Banerjee
A General Framework For Detecting Anomalous Inputs to DNN Classifiers. ICML (2021)
Robi Bhattacharjee, Somesh Jha, Kamalika Chaudhuri
Sample Complexity of Adversarially Robust Linear Classification on Separated Data. CoRR (2020)
Jayaram Raghuram, Varun Chandrasekaran, Somesh Jha, Suman Banerjee
Detecting Anomalous Inputs to DNN Classifiers By Joint Statistical Testing at the Layers. CoRR (2020)
Tianhao Wang, Min Xu, Bolin Ding, Jingren Zhou, Cheng Hong, Zhicong Huang, Ninghui Li, Somesh Jha
Improving Utility and Security of the Shuffler-based Differential Privacy. Proc. VLDB Endow. 13 (13) (2020)
Uyeong Jang, Susmit Jha, Somesh Jha
On the Need for Topology-Aware Generative Models for Manifold-Based Defenses. ICLR (2020)
Samuel Yeom, Irene Giacomelli, Alan Menaged, Matt Fredrikson, Somesh Jha
Overfitting, robustness, and malicious algorithms: A study of potential causes of privacy risk in machine learning. J. Comput. Secur. 28 (1) (2020)
Jiefeng Chen, Yixuan Li, Xi Wu, Yingyu Liang, Somesh Jha
Robust Out-of-distribution Detection in Neural Networks. CoRR (2020)
Sanjam Garg, Somesh Jha, Saeed Mahloujifar, Mohammad Mahmoody
Adversarially Robust Learning Could Leverage Computational Hardness. ALT (2020)
Aiping Xiong, Tianhao Wang, Ninghui Li, Somesh Jha
Towards Effective Differential Privacy Communication for Users' Data Sharing Decision and Comprehension. IEEE Symposium on Security and Privacy (2020)
Goutham Ramakrishnan, Jordan Henkel, Zi Wang, Aws Albarghouthi, Somesh Jha, Thomas W. Reps
Semantic Robustness of Models of Source Code. CoRR (2020)
Amrita Roy Chowdhury, Bolin Ding, Somesh Jha, Weiran Liu, Jingren Zhou
Intertwining Order Preserving Encryption and Differential Privacy. CoRR (2020)

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Publication Activity (10 Years)

Top Topics

Top Venues

Somesh Jha