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ORCIDSomesh Jha
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- affiliation: University of Wisconsin-Madison, Madison, USA
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2020 – today
- 2024
[j42]Samarjit Chakraborty
, Somesh Jha, Soheil Samii, Philipp Mundhenk:
Introduction to the Special Issue on Automotive CPS Safety & Security: Part 2. ACM Trans. Cyber Phys. Syst. 8(2): 10 (2024)- [j41]Jiefeng Chen, Jinsung Yoon, Sayna Ebrahimi, Sercan Ö. Arik, Somesh Jha, Tomas Pfister:
ASPEST: Bridging the Gap Between Active Learning and Selective Prediction. Trans. Mach. Learn. Res. 2024 (2024) - [c193]Neal Mangaokar, Ashish Hooda, Jihye Choi, Shreyas Chandrashekaran, Kassem Fawaz, Somesh Jha, Atul Prakash:
PRP: Propagating Universal Perturbations to Attack Large Language Model Guard-Rails. ACL (1) 2024: 10960-10976 - [c192]Zi Wang, Bin Hu, Aaron J. Havens, Alexandre Araujo, Yang Zheng, Yudong Chen, Somesh Jha:
On the Scalability and Memory Efficiency of Semidefinite Programs for Lipschitz Constant Estimation of Neural Networks. ICLR 2024 - [c191]Ashish Hooda, Mihai Christodorescu, Miltiadis Allamanis, Aaron Wilson, Kassem Fawaz, Somesh Jha:
Do Large Code Models Understand Programming Concepts? Counterfactual Analysis for Code Predicates. ICML 2024 - [c190]Nils Palumbo, Yang Guo, Xi Wu, Jiefeng Chen, Yingyu Liang, Somesh Jha:
Two Heads are Actually Better than One: Towards Better Adversarial Robustness via Transduction and Rejection. ICML 2024 - [c189]Ashish Hooda, Neal Mangaokar, Ryan Feng, Kassem Fawaz, Somesh Jha, Atul Prakash:
D4: Detection of Adversarial Diffusion Deepfakes Using Disjoint Ensembles. WACV 2024: 3800-3810 - [i112]Ashish Hooda, Mihai Christodorescu, Miltiadis Allamanis, Aaron Wilson, Kassem Fawaz, Somesh Jha:
Do Large Code Models Understand Programming Concepts? A Black-box Approach. CoRR abs/2402.05980 (2024) - [i111]Neal Mangaokar, Ashish Hooda, Jihye Choi, Shreyas Chandrashekaran, Kassem Fawaz, Somesh Jha, Atul Prakash:
PRP: Propagating Universal Perturbations to Attack Large Language Model Guard-Rails. CoRR abs/2402.15911 (2024) - [i110]Fangzhou Wu, Ning Zhang, Somesh Jha, Patrick D. McDaniel, Chaowei Xiao:
A New Era in LLM Security: Exploring Security Concerns in Real-World LLM-based Systems. CoRR abs/2402.18649 (2024) - [i109]Mihai Christodorescu, Ryan Craven, Soheil Feizi, Neil Gong, Mia Hoffmann, Somesh Jha, Zhengyuan Jiang, Mehrdad Saberi Kamarposhti, John C. Mitchell, Jessica Newman, Emelia Probasco, Yanjun Qi, Khawaja Shams, Matthew Turek:
Securing the Future of GenAI: Policy and Technology. CoRR abs/2407.12999 (2024) - [i108]Nils Palumbo, Ravi Mangal, Zifan Wang, Saranya Vijayakumar, Corina S. Pasareanu, Somesh Jha:
Mechanistically Interpreting a Transformer-based 2-SAT Solver: An Axiomatic Approach. CoRR abs/2407.13594 (2024) - [i107]Jihye Choi, Nils Palumbo, Prasad Chalasani, Matthew M. Engelhard, Somesh Jha, Anivarya Kumar, David Page:
MALADE: Orchestration of LLM-powered Agents with Retrieval Augmented Generation for Pharmacovigilance. CoRR abs/2408.01869 (2024) - [i106]Ashish Hooda, Rishabh Khandelwal, Prasad Chalasani, Kassem Fawaz, Somesh Jha:
PolicyLR: A Logic Representation For Privacy Policies. CoRR abs/2408.14830 (2024) - [i105]Zi Wang, Divyam Anshumaan, Ashish Hooda, Yudong Chen, Somesh Jha:
Functional Homotopy: Smoothing Discrete Optimization via Continuous Parameters for LLM Jailbreak Attacks. CoRR abs/2410.04234 (2024) - [i104]Xiaogeng Liu, Peiran Li, Edward Suh, Yevgeniy Vorobeychik, Zhuoqing Mao, Somesh Jha, Patrick McDaniel, Huan Sun, Bo Li, Chaowei Xiao:
AutoDAN-Turbo: A Lifelong Agent for Strategy Self-Exploration to Jailbreak LLMs. CoRR abs/2410.05295 (2024) - [i103]Xuandong Zhao, Sam Gunn, Miranda Christ, Jaiden Fairoze, Andres Fabrega, Nicholas Carlini, Sanjam Garg, Sanghyun Hong, Milad Nasr, Florian Tramèr, Somesh Jha, Lei Li, Yu-Xiang Wang, Dawn Song:
SoK: Watermarking for AI-Generated Content. CoRR abs/2411.18479 (2024) - [i102]Jihye Choi, Jayaram Raghuram, Yixuan Li, Somesh Jha:
Adaptive Concept Bottleneck for Foundation Models Under Distribution Shifts. CoRR abs/2412.14097 (2024) - [i101]Mihai Christodorescu, Ryan Craven, Soheil Feizi, Neil Zhenqiang Gong, Mia Hoffmann, Somesh Jha, Zhengyuan Jiang, Mehrdad Saberi Kamarposhti, John C. Mitchell, Jessica Newman, Emelia Probasco, Yanjun Qi, Khawaja Shams, Matthew Turek:
Securing the Future of GenAI: Policy and Technology. IACR Cryptol. ePrint Arch. 2024: 855 (2024) - 2023
- [j40]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): 1-52 (2023) - [j39]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): 527-555 (2023) - [j38]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): 1:1-1:6 (2023) - [j37]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): 2761-2775 (2023) - [c188]Joann Qiongna Chen, Tianhao Wang, Zhikun Zhang, Yang Zhang, Somesh Jha, Zhou Li:
Differentially Private Resource Allocation. ACSAC 2023: 772-786 - [c187]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: 786-800 - [c186]Sanjam Garg, Aarushi Goel, Somesh Jha, Saeed Mahloujifar, Mohammad Mahmoody, Guru-Vamsi Policharla, Mingyuan Wang:
Experimenting with Zero-Knowledge Proofs of Training. CCS 2023: 1880-1894 - [c185]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: 5190-5213 - [c184]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 - [c183]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 - [c182]Jiefeng Chen, Jayaram Raghuram, Jihye Choi, Xi Wu, Yingyu Liang, Somesh Jha:
Stratified Adversarial Robustness with Rejection. ICML 2023: 4867-4894 - [c181]Jihye Choi, Jayaram Raghuram, Ryan Feng, Jiefeng Chen, Somesh Jha, Atul Prakash:
Concept-based Explanations for Out-of-Distribution Detectors. ICML 2023: 5817-5837 - [c180]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 - [c179]Zifan Wang, Saranya Vijayakumar, Kaiji Lu, Vijay Ganesh, Somesh Jha, Matt Fredrikson:
Grounding Neural Inference with Satisfiability Modulo Theories. NeurIPS 2023 - [c178]Washington Garcia, Pin-Yu Chen, Hamilton Scott Clouse, Somesh Jha, Kevin R. B. Butler:
Less is More: Dimension Reduction Finds On-Manifold Adversarial Examples in Hard-Label Attacks. SaTML 2023: 254-270 - [c177]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: 1596-1612 - [c176]Harrison Rosenberg, Brian Tang, Kassem Fawaz, Somesh Jha:
Fairness Properties of Face Recognition and Obfuscation Systems. USENIX Security Symposium 2023: 7231-7248 - [i100]Matt Fredrikson, Kaiji Lu, Saranya Vijayakumar, Somesh Jha, Vijay Ganesh, Zifan Wang:
Learning Modulo Theories. CoRR abs/2301.11435 (2023) - [i99]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 abs/2302.00120 (2023) - [i98]Somesh Jha, Mihai Christodorescu, Anh Pham:
Formal Analysis of the API Proxy Problem. CoRR abs/2302.13525 (2023) - [i97]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 abs/2303.00106 (2023) - [i96]Ryan Feng, Ashish Hooda, Neal Mangaokar, Kassem Fawaz, Somesh Jha, Atul Prakash:
Investigating Stateful Defenses Against Black-Box Adversarial Examples. CoRR abs/2303.06280 (2023) - [i95]Zi Wang, Somesh Jha, Krishnamurthy Dvijotham:
Efficient Symbolic Reasoning for Neural-Network Verification. CoRR abs/2303.13588 (2023) - [i94]Jiefeng Chen, Jinsung Yoon, Sayna Ebrahimi, Sercan Ö. Arik, Somesh Jha, Tomas Pfister:
ASPEST: Bridging the Gap Between Active Learning and Selective Prediction. CoRR abs/2304.03870 (2023) - [i93]Jiefeng Chen, Jayaram Raghuram, Jihye Choi, Xi Wu, Yingyu Liang, Somesh Jha:
Stratified Adversarial Robustness with Rejection. CoRR abs/2305.01139 (2023) - [i92]Zi Wang, Jihye Choi, Somesh Jha:
Rethink Diversity in Deep Learning Testing. CoRR abs/2305.15698 (2023) - [i91]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 abs/2305.17528 (2023) - [i90]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 abs/2307.01292 (2023) - [i89]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 abs/2307.16331 (2023) - [i88]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 abs/2308.14840 (2023) - [i87]Mohannad Alhanahnah, Philipp Dominik Schubert, Thomas W. Reps, Somesh Jha, Eric Bodden:
slash: A Technique for Static Configuration-Logic Identification. CoRR abs/2310.06758 (2023) - [i86]Jihye Choi, Shruti Tople, Varun Chandrasekaran, Somesh Jha:
Why Train More? Effective and Efficient Membership Inference via Memorization. CoRR abs/2310.08015 (2023) - [i85]Jiefeng Chen, Jinsung Yoon, Sayna Ebrahimi, Sercan Ö. Arik, Tomas Pfister, Somesh Jha:
Adaptation with Self-Evaluation to Improve Selective Prediction in LLMs. CoRR abs/2310.11689 (2023) - [i84]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 abs/2310.16678 (2023) - [i83]Jaiden Fairoze, Sanjam Garg, Somesh Jha, Saeed Mahloujifar, Mohammad Mahmoody, Mingyuan Wang:
Publicly Detectable Watermarking for Language Models. CoRR abs/2310.18491 (2023) - [i82]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 abs/2311.04824 (2023) - [i81]Mingtian Tan, Tianhao Wang, Somesh Jha:
A Somewhat Robust Image Watermark against Diffusion-based Editing Models. CoRR abs/2311.13713 (2023) - [i80]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: 1345 (2023) - [i79]Jaiden Fairoze, Sanjam Garg, Somesh Jha, Saeed Mahloujifar, Mohammad Mahmoody, Mingyuan Wang:
Publicly Detectable Watermarking for Language Models. IACR Cryptol. ePrint Arch. 2023: 1661 (2023) - 2022
- [j36]Vijay Ganesh, Sanjit A. Seshia, Somesh Jha:
Machine learning and logic: a new frontier in artificial intelligence. Formal Methods Syst. Des. 60(3): 426-451 (2022) - [j35]Zi Wang, Aws Albarghouthi, Gautam Prakriya, Somesh Jha:
Interval universal approximation for neural networks. Proc. ACM Program. Lang. 6(POPL): 1-29 (2022) - [c175]Samuel Maddock, Graham Cormode, Tianhao Wang, Carsten Maple, Somesh Jha:
Federated Boosted Decision Trees with Differential Privacy. CCS 2022: 2249-2263 - [c174]Amrita Roy Chowdhury, Bolin Ding, Somesh Jha, Weiran Liu, Jingren Zhou:
Strengthening Order Preserving Encryption with Differential Privacy. CCS 2022: 2519-2533 - [c173]Amrita Roy Chowdhury, Chuan Guo, Somesh Jha, Laurens van der Maaten:
EIFFeL: Ensuring Integrity for Federated Learning. CCS 2022: 2535-2549 - [c172]Mohannad Alhanahnah, Rithik Jain, Vaibhav Rastogi, Somesh Jha, Thomas W. Reps:
Lightweight, Multi-Stage, Compiler-Assisted Application Specialization. EuroS&P 2022: 251-269 - [c171]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: 664-683 - [c170]Jiefeng Chen, Xi Wu, Yang Guo, Yingyu Liang, Somesh Jha:
Towards Evaluating the Robustness of Neural Networks Learned by Transduction. ICLR 2022 - [c169]Casey Meehan, Amrita Roy Chowdhury, Kamalika Chaudhuri, Somesh Jha:
Privacy Implications of Shuffling. ICLR 2022 - [c168]Sanjam Garg, Somesh Jha, Saeed Mahloujifar, Mohammad Mahmoody, Mingyuan Wang:
Overparameterization from Computational Constraints. NeurIPS 2022 - [c167]Yizhen Wang, Mohannad Alhanahnah, Xiaozhu Meng, Ke Wang, Mihai Christodorescu, Somesh Jha:
Robust Learning against Relational Adversaries. NeurIPS 2022 - [c166]Zi Wang, Gautam Prakriya, Somesh Jha:
A Quantitative Geometric Approach to Neural-Network Smoothness. NeurIPS 2022 - [c165]Jordan Henkel, Goutham Ramakrishnan, Zi Wang, Aws Albarghouthi, Somesh Jha, Thomas W. Reps:
Semantic Robustness of Models of Source Code. SANER 2022: 526-537 - [i78]Harrison Rosenberg, Robi Bhattacharjee, Kassem Fawaz, Somesh Jha:
An Exploration of Multicalibration Uniform Convergence Bounds. CoRR abs/2202.04530 (2022) - [i77]Ashish Hooda, Neal Mangaokar, Ryan Feng, Kassem Fawaz, Somesh Jha, Atul Prakash:
Towards Adversarially Robust Deepfake Detection: An Ensemble Approach. CoRR abs/2202.05687 (2022) - [i76]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 abs/2202.10014 (2022) - [i75]Zi Wang, Gautam Prakriya, Somesh Jha:
A Quantitative Geometric Approach to Neural Network Smoothness. CoRR abs/2203.01212 (2022) - [i74]Jihye Choi, Jayaram Raghuram, Ryan Feng, Jiefeng Chen, Somesh Jha, Atul Prakash:
Concept-based Explanations for Out-Of-Distribution Detectors. CoRR abs/2203.02586 (2022) - [i73]Saeed Mahloujifar, Alexandre Sablayrolles, Graham Cormode, Somesh Jha:
Optimal Membership Inference Bounds for Adaptive Composition of Sampled Gaussian Mechanisms. CoRR abs/2204.06106 (2022) - [i72]Ryan Feng, Somesh Jha, Atul Prakash:
Constraining the Attack Space of Machine Learning Models with Distribution Clamping Preprocessing. CoRR abs/2205.08989 (2022) - [i71]Sanjam Garg, Somesh Jha, Saeed Mahloujifar, Mohammad Mahmoody, Mingyuan Wang:
Overparameterized (robust) models from computational constraints. CoRR abs/2208.12926 (2022) - [i70]Samuel Maddock, Graham Cormode, Tianhao Wang, Carsten Maple, Somesh Jha:
Federated Boosted Decision Trees with Differential Privacy. CoRR abs/2210.02910 (2022) - [i69]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 abs/2211.15410 (2022) - [i68]Sébastien Bardin, Somesh Jha, Vijay Ganesh:
Machine Learning and Logical Reasoning: The New Frontier (Dagstuhl Seminar 22291). Dagstuhl Reports 12(7): 80-111 (2022) - 2021
- [j34]Kim G. Larsen, Natarajan Shankar, Pierre Wolper, Somesh Jha:
2018 CAV award. Formal Methods Syst. Des. 57(1): 116-117 (2021) - [j33]Varun Chandrasekaran, Chuhan Gao, Brian Tang, Kassem Fawaz, Somesh Jha, Suman Banerjee:
Face-Off: Adversarial Face Obfuscation. Proc. Priv. Enhancing Technol. 2021(2): 369-390 (2021) - [j32]Tianhao Wang, Ninghui Li, Somesh Jha:
Locally Differentially Private Heavy Hitter Identification. IEEE Trans. Dependable Secur. Comput. 18(2): 982-993 (2021) - [j31]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: 4363-4376 (2021) - [c164]Somesh Jha:
Trustworthy Machine Learning: Past, Present, and Future. AsiaCCS 2021: 1 - [c163]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: 1237-1253 - [c162]Washington Garcia, Animesh Chhotaray, Joseph I. Choi, Suman Kalyan Adari, Kevin R. B. Butler, Somesh Jha:
Brittle Features of Device Authentication. CODASPY 2021: 53-64 - [c161]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 - [c160]Robi Bhattacharjee, Somesh Jha, Kamalika Chaudhuri:
Sample Complexity of Robust Linear Classification on Separated Data. ICML 2021: 884-893 - [c159]Jayaram Raghuram, Varun Chandrasekaran, Somesh Jha, Suman Banerjee:
A General Framework For Detecting Anomalous Inputs to DNN Classifiers. ICML 2021: 8764-8775 - [c158]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: 10862-10875 - [c157]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: 14980-14992 - [c156]Jiefeng Chen, Yixuan Li, Xi Wu, Yingyu Liang, Somesh Jha:
ATOM: Robustifying Out-of-Distribution Detection Using Outlier Mining. ECML/PKDD (3) 2021: 430-445 - [c155]Nicholas Carlini, Samuel Deng, Sanjam Garg, Somesh Jha, Saeed Mahloujifar, Mohammad Mahmoody, Abhradeep Thakurta, Florian Tramèr:
Is Private Learning Possible with Instance Encoding? SP 2021: 410-427 - [i67]Christopher A. Choquette-Choo, Natalie Dullerud, Adam Dziedzic, Yunxiang Zhang, Somesh Jha, Nicolas Papernot, Xiao Wang:
CaPC Learning: Confidential and Private Collaborative Learning. CoRR abs/2102.05188 (2021) - [i66]Thomas Kobber Panum, Zi Wang, Pengyu Kan, Earlence Fernandes, Somesh Jha:
Exploring Adversarial Robustness of Deep Metric Learning. CoRR abs/2102.07265 (2021) - [i65]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 abs/2103.03325 (2021) - [i64]Varun Chandrasekaran, Darren Edge, Somesh Jha, Amit Sharma, Cheng Zhang, Shruti Tople:
Causally Constrained Data Synthesis for Private Data Release. CoRR abs/2105.13144 (2021) - [i63]Casey Meehan, Amrita Roy Chowdhury, Kamalika Chaudhuri, Somesh Jha:
A Shuffling Framework for Local Differential Privacy. CoRR abs/2106.06603 (2021) - [i62]Jiefeng Chen, Yang Guo, Xi Wu, Tianqi Li, Qicheng Lao, Yingyu Liang, Somesh Jha:
Towards Adversarial Robustness via Transductive Learning. CoRR abs/2106.08387 (2021) - [i61]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 abs/2106.15728 (2021) - [i60]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 abs/2108.00874 (2021) - [i59]Harrison Rosenberg, Brian Tang, Kassem Fawaz, Somesh Jha:
Fairness Properties of Face Recognition and Obfuscation Systems. CoRR abs/2108.02707 (2021) - [i58]Nicholas Carlini, Sanjam Garg, Somesh Jha, Saeed Mahloujifar, Mohammad Mahmoody, Florian Tramèr:
NeuraCrypt is not private. CoRR abs/2108.07256 (2021) - [i57]Mohannad Alhanahnah, Rithik Jain, Vaibhav Rastogi, Somesh Jha, Thomas W. Reps:
Lightweight, Multi-Stage, Compiler-Assisted Application Specialization. CoRR abs/2109.02775 (2021) - [i56]Jiefeng Chen, Xi Wu, Yang Guo, Yingyu Liang, Somesh Jha:
Towards Evaluating the Robustness of Neural Networks Learned by Transduction. CoRR abs/2110.14735 (2021) - [i55]Amrita Roy Chowdhury, Chuan Guo, Somesh Jha, Laurens van der Maaten:
EIFFeL: Ensuring Integrity for Federated Learning. CoRR abs/2112.12727 (2021) - 2020
- [j30]Sanjit A. Seshia, Somesh Jha, Tommaso Dreossi:
Semantic Adversarial Deep Learning. IEEE Des. Test 37(2): 8-18 (2020) - [j29]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): 35-70 (2020) - [j28]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): 3545-3558 (2020) - [c154]Sanjam Garg, Somesh Jha, Saeed Mahloujifar, Mohammad Mahmoody:
Adversarially Robust Learning Could Leverage Computational Hardness. ALT 2020: 364-385 - [c153]Uyeong Jang, Susmit Jha, Somesh Jha:
On the Need for Topology-Aware Generative Models for Manifold-Based Defenses. ICLR 2020 - [c152]Prasad Chalasani, Jiefeng Chen, Amrita Roy Chowdhury, Xi Wu, Somesh Jha:
Concise Explanations of Neural Networks using Adversarial Training. ICML 2020: 1383-1391 - [c151]Amrita Roy Chowdhury, Theodoros Rekatsinas, Somesh Jha:
Data-Dependent Differentially Private Parameter Learning for Directed Graphical Models. ICML 2020: 1939-1951 - [c150]Wei Zhang, Thomas Kobber Panum, Somesh Jha, Prasad Chalasani, David Page:
CAUSE: Learning Granger Causality from Event Sequences using Attribution Methods. ICML 2020: 11235-11245 - [c149]Amrita Roy Chowdhury, Chenghong Wang, Xi He, Ashwin Machanavajjhala, Somesh Jha:
Crypt?: Crypto-Assisted Differential Privacy on Untrusted Servers. SIGMOD Conference 2020: 603-619 - [c148]Aiping Xiong, Tianhao Wang, Ninghui Li, Somesh Jha:
Towards Effective Differential Privacy Communication for Users' Data Sharing Decision and Comprehension. SP 2020: 392-410 - [c147]Zhichuang Sun, Bo Feng, Long Lu, Somesh Jha:
OAT: Attesting Operation Integrity of Embedded Devices. SP 2020: 1433-1449 - [c146]Varun Chandrasekaran, Kamalika Chaudhuri, Irene Giacomelli, Somesh Jha, Songbai Yan:
Exploring Connections Between Active Learning and Model Extraction. USENIX Security Symposium 2020: 1309-1326 - [i54]Goutham Ramakrishnan, Jordan Henkel, Zi Wang, Aws Albarghouthi, Somesh Jha, Thomas W. Reps:
Semantic Robustness of Models of Source Code. CoRR abs/2002.03043 (2020) - [i53]Ryan Feng, Jiefeng Chen, Nelson R. Manohar, Earlence Fernandes, Somesh Jha, Atul Prakash:
Query-Efficient Physical Hard-Label Attacks on Deep Learning Visual Classification. CoRR abs/2002.07088 (2020) - [i52]Wei Zhang, Thomas Kobber Panum, Somesh Jha, Prasad Chalasani, David Page:
CAUSE: Learning Granger Causality from Event Sequences using Attribution Methods. CoRR abs/2002.07906 (2020) - [i51]Yue Gao, Harrison Rosenberg, Kassem Fawaz, Somesh Jha, Justin Hsu:
Analyzing Accuracy Loss in Randomized Smoothing Defenses. CoRR abs/2003.01595 (2020) - [i50]Chuhan Gao, Varun Chandrasekaran, Kassem Fawaz, Somesh Jha:
Face-Off: Adversarial Face Obfuscation. CoRR abs/2003.08861 (2020) - [i49]Jiefeng Chen, Yixuan Li, Xi Wu, Yingyu Liang, Somesh Jha:
Robust Out-of-distribution Detection in Neural Networks. CoRR abs/2003.09711 (2020) - [i48]Sanjam Garg, Somesh Jha, Saeed Mahloujifar, Mohammad Mahmoody, Abhradeep Thakurta:
Obliviousness Makes Poisoning Adversaries Weaker. CoRR abs/2003.12020 (2020) - [i47]Aiping Xiong, Tianhao Wang, Ninghui Li, Somesh Jha:
Towards Effective Differential Privacy Communication for Users' Data Sharing Decision and Comprehension. CoRR abs/2003.13922 (2020) - [i46]Xi Wu, Yang Guo, Jiefeng Chen, Yingyu Liang, Somesh Jha, Prasad Chalasani:
Representation Bayesian Risk Decompositions and Multi-Source Domain Adaptation. CoRR abs/2004.10390 (2020) - [i45]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. CoRR abs/2005.11753 (2020) - [i44]Jiefeng Chen, Yixuan Li, Xi Wu, Yingyu Liang, Somesh Jha:
Robust Out-of-distribution Detection via Informative Outlier Mining. CoRR abs/2006.15207 (2020) - [i43]Yizhen Wang, Xiaozhu Meng, Mihai Christodorescu, Somesh Jha:
Robust Learning against Logical Adversaries. CoRR abs/2007.00772 (2020) - [i42]Zi Wang, Aws Albarghouthi, Somesh Jha:
Abstract Universal Approximation for Neural Networks. CoRR abs/2007.06093 (2020) - [i41]Jayaram Raghuram, Varun Chandrasekaran, Somesh Jha, Suman Banerjee:
Detecting Anomalous Inputs to DNN Classifiers By Joint Statistical Testing at the Layers. CoRR abs/2007.15147 (2020) - [i40]Amrita Roy Chowdhury, Bolin Ding, Somesh Jha, Weiran Liu, Jingren Zhou:
Intertwining Order Preserving Encryption and Differential Privacy. CoRR abs/2009.05679 (2020) - [i39]Nicholas Carlini, Samuel Deng, Sanjam Garg, Somesh Jha, Saeed Mahloujifar, Mohammad Mahmoody, Shuang Song, Abhradeep Thakurta, Florian Tramèr:
An Attack on InstaHide: Is Private Learning Possible with Instance Encoding? CoRR abs/2011.05315 (2020) - [i38]Zhichuang Sun, Ruimin Sun, Long Lu, Somesh Jha:
ShadowNet: A Secure and Efficient System for On-device Model Inference. CoRR abs/2011.05905 (2020) - [i37]Robi Bhattacharjee, Somesh Jha, Kamalika Chaudhuri:
Sample Complexity of Adversarially Robust Linear Classification on Separated Data. CoRR abs/2012.10794 (2020)
2010 – 2019
- 2019
- [c145]Jiefeng Chen, Xi Wu, Vaibhav Rastogi, Yingyu Liang, Somesh Jha:
Towards Understanding Limitations of Pixel Discretization Against Adversarial Attacks. EuroS&P 2019: 480-495 - [c144]Susmit Jha, Sunny Raj, Steven Lawrence Fernandes, Sumit Kumar Jha, Somesh Jha, Brian Jalaian, Gunjan Verma, Ananthram Swami:
Attribution-Based Confidence Metric For Deep Neural Networks. NeurIPS 2019: 11826-11837 - [c143]Jiefeng Chen, Xi Wu, Vaibhav Rastogi, Yingyu Liang, Somesh Jha:
Robust Attribution Regularization. NeurIPS 2019: 14300-14310 - [c142]Tianhao Wang, Bolin Ding, Jingren Zhou, Cheng Hong, Zhicong Huang, Ninghui Li, Somesh Jha:
Answering Multi-Dimensional Analytical Queries under Local Differential Privacy. SIGMOD Conference 2019: 159-176 - [i36]Amrita Roy Chowdhury, Chenghong Wang, Xi He, Ashwin Machanavajjhala, Somesh Jha:
Outis: Crypto-Assisted Differential Privacy on Untrusted Servers. CoRR abs/1902.07756 (2019) - [i35]Susmit Jha, Sunny Raj, Steven Lawrence Fernandes, Sumit Kumar Jha, Somesh Jha, Gunjan Verma, Brian Jalaian, Ananthram Swami:
Attribution-driven Causal Analysis for Detection of Adversarial Examples. CoRR abs/1903.05821 (2019) - [i34]Jiefeng Chen, Xi Wu, Vaibhav Rastogi, Yingyu Liang, Somesh Jha:
Robust Attribution Regularization. CoRR abs/1905.09957 (2019) - [i33]Varun Chandrasekaran, Brian Tang, Varsha Pendyala, Kassem Fawaz, Somesh Jha, Xi Wu:
Enhancing ML Robustness Using Physical-World Constraints. CoRR abs/1905.10900 (2019) - [i32]Sanjam Garg, Somesh Jha, Saeed Mahloujifar, Mohammad Mahmoody:
Adversarially Robust Learning Could Leverage Computational Hardness. CoRR abs/1905.11564 (2019) - [i31]Amrita Roy Chowdhury, Theodoros Rekatsinas, Somesh Jha:
Data-Dependent Differentially Private Parameter Learning for Directed Graphical Models. CoRR abs/1905.12813 (2019) - [i30]Tianhao Wang, Min Xu, Bolin Ding, Jingren Zhou, Ninghui Li, Somesh Jha:
Practical and Robust Privacy Amplification with Multi-Party Differential Privacy. CoRR abs/1908.11515 (2019) - [i29]Uyeong Jang, Susmit Jha, Somesh Jha:
On Need for Topology Awareness of Generative Models. CoRR abs/1909.03334 (2019) - [i28]Lakshya Jain, Wilson Wu, Steven Chen, Uyeong Jang, Varun Chandrasekaran, Sanjit A. Seshia, Somesh Jha:
Generating Semantic Adversarial Examples with Differentiable Rendering. CoRR abs/1910.00727 (2019) - 2018
- [j27]Irfan Ul Haq, Sergio Chica, Juan Caballero, Somesh Jha:
Malware lineage in the wild. Comput. Secur. 78: 347-363 (2018) - [c141]Irene Giacomelli, Somesh Jha, Marc Joye, C. David Page, Kyonghwan Yoon:
Privacy-Preserving Ridge Regression with only Linearly-Homomorphic Encryption. ACNS 2018: 243-261 - [c140]Tommaso Dreossi, Somesh Jha, Sanjit A. Seshia:
Semantic Adversarial Deep Learning. CAV (1) 2018: 3-26 - [c139]Samuel Yeom, Irene Giacomelli, Matt Fredrikson, Somesh Jha:
Privacy Risk in Machine Learning: Analyzing the Connection to Overfitting. CSF 2018: 268-282 - [c138]Yizhen Wang, Somesh Jha, Kamalika Chaudhuri:
Analyzing the Robustness of Nearest Neighbors to Adversarial Examples. ICML 2018: 5120-5129 - [c137]Xi Wu, Uyeong Jang, Jiefeng Chen, Lingjiao Chen, Somesh Jha:
Reinforcing Adversarial Robustness using Model Confidence Induced by Adversarial Training. ICML 2018: 5330-5338 - [c136]Andrew Miller, Zhicheng Cai, Somesh Jha:
Smart Contracts and Opportunities for Formal Methods. ISoLA (4) 2018: 280-299 - [c135]Susmit Jha, Uyeong Jang, Somesh Jha, Brian Jalaian:
Detecting Adversarial Examples Using Data Manifolds. MILCOM 2018: 547-552 - [c134]Yonghwi Kwon, Fei Wang, Weihang Wang, Kyu Hyung Lee, Wen-Chuan Lee, Shiqing Ma, Xiangyu Zhang, Dongyan Xu, Somesh Jha, Gabriela F. Ciocarlie, Ashish Gehani, Vinod Yegneswaran:
MCI : Modeling-based Causality Inference in Audit Logging for Attack Investigation. NDSS 2018 - [c133]Graham Cormode, Somesh Jha, Tejas Kulkarni, Ninghui Li, Divesh Srivastava, Tianhao Wang:
Privacy at Scale: Local Differential Privacy in Practice. SIGMOD Conference 2018: 1655-1658 - [c132]Jinman Zhao, Aws Albarghouthi, Vaibhav Rastogi, Somesh Jha, Damien Octeau:
Neural-augmented static analysis of Android communication. ESEC/SIGSOFT FSE 2018: 342-353 - [c131]Tianhao Wang, Ninghui Li, Somesh Jha:
Locally Differentially Private Frequent Itemset Mining. IEEE Symposium on Security and Privacy 2018: 127-143 - [c130]Shiqing Ma, Juan Zhai, Yonghwi Kwon, Kyu Hyung Lee, Xiangyu Zhang, Gabriela F. Ciocarlie, Ashish Gehani, Vinod Yegneswaran, Dongyan Xu, Somesh Jha:
Kernel-Supported Cost-Effective Audit Logging for Causality Tracking. USENIX ATC 2018: 241-254 - [i27]Zhichuang Sun, Bo Feng, Long Lu, Somesh Jha:
OEI: Operation Execution Integrity for Embedded Devices. CoRR abs/1802.03462 (2018) - [i26]Tommaso Dreossi, Somesh Jha, Sanjit A. Seshia:
Semantic Adversarial Deep Learning. CoRR abs/1804.07045 (2018) - [i25]Jiefeng Chen, Xi Wu, Yingyu Liang, Somesh Jha:
Improving Adversarial Robustness by Data-Specific Discretization. CoRR abs/1805.07816 (2018) - [i24]Jinman Zhao, Aws Albarghouthi, Vaibhav Rastogi, Somesh Jha, Damien Octeau:
Neural-Augmented Static Analysis of Android Communication. CoRR abs/1809.04059 (2018) - [i23]Xiaozhu Meng, Barton P. Miller, Somesh Jha:
Adversarial Binaries for Authorship Identification. CoRR abs/1809.08316 (2018) - [i22]Washington Garcia, Joseph I. Choi, Suman Kalyan Adari, Somesh Jha, Kevin R. B. Butler:
Explainable Black-Box Attacks Against Model-based Authentication. CoRR abs/1810.00024 (2018) - [i21]Prasad Chalasani, Jiefeng Chen, Amrita Roy Chowdhury, Somesh Jha, Xi Wu:
Concise Explanations of Neural Networks using Adversarial Training. CoRR abs/1810.06583 (2018) - [i20]Varun Chandrasekaran, Kamalika Chaudhuri, Irene Giacomelli, Somesh Jha, Songbai Yan:
Model Extraction and Active Learning. CoRR abs/1811.02054 (2018) - [i19]Irene Giacomelli, Somesh Jha, Ross Kleiman, David Page, Kyonghwan Yoon:
Privacy-Preserving Collaborative Prediction using Random Forests. CoRR abs/1811.08695 (2018) - 2017
- [j26]William R. Harris, Somesh Jha, Thomas W. Reps, Sanjit A. Seshia:
Program synthesis for interactive-security systems. Formal Methods Syst. Des. 51(2): 362-394 (2017) - [c129]Uyeong Jang, Xi Wu, Somesh Jha:
Objective Metrics and Gradient Descent Algorithms for Adversarial Examples in Machine Learning. ACSAC 2017: 262-277 - [c128]Vaibhav Rastogi, Chaitra Niddodi, Sibin Mohan, Somesh Jha:
New Directions for Container Debloating. FEAST@CCS 2017: 51-56 - [c127]Nicolas Papernot, Patrick D. McDaniel, Ian J. Goodfellow, Somesh Jha, Z. Berkay Celik, Ananthram Swami:
Practical Black-Box Attacks against Machine Learning. AsiaCCS 2017: 506-519 - [c126]Drew Davidson, Yaohui Chen, Franklin George, Long Lu, Somesh Jha:
Secure Integration of Web Content and Applications on Commodity Mobile Operating Systems. AsiaCCS 2017: 652-665 - [c125]Lorenzo De Carli, Ruben Torres, Gaspar Modelo-Howard, Alok Tongaonkar, Somesh Jha:
Botnet protocol inference in the presence of encrypted traffic. INFOCOM 2017: 1-9 - [c124]Lorenzo De Carli, Ruben Torres, Gaspar Modelo-Howard, Alok Tongaonkar, Somesh Jha:
Kali: Scalable encryption fingerprinting in dynamic malware traces. MALWARE 2017: 3-10 - [c123]Drew Davidson, Vaibhav Rastogi, Mihai Christodorescu, Somesh Jha:
Enhancing Android Security Through App Splitting. SecureComm 2017: 24-44 - [c122]Xi Wu, Fengan Li, Arun Kumar, Kamalika Chaudhuri, Somesh Jha, Jeffrey F. Naughton:
Bolt-on Differential Privacy for Scalable Stochastic Gradient Descent-based Analytics. SIGMOD Conference 2017: 1307-1322 - [c121]Vaibhav Rastogi, Drew Davidson, Lorenzo De Carli, Somesh Jha, Patrick D. McDaniel:
Cimplifier: automatically debloating containers. ESEC/SIGSOFT FSE 2017: 476-486 - [c120]Tianhao Wang, Jeremiah Blocki, Ninghui Li, Somesh Jha:
Locally Differentially Private Protocols for Frequency Estimation. USENIX Security Symposium 2017: 729-745 - [i18]Rathijit Sen, Jianqiao Zhu, Jignesh M. Patel, Somesh Jha:
ROSA: R Optimizations with Static Analysis. CoRR abs/1704.02996 (2017) - [i17]Tianhao Wang, Jeremiah Blocki, Ninghui Li, Somesh Jha:
Optimizing Locally Differentially Private Protocols. CoRR abs/1705.04421 (2017) - [i16]Yizhen Wang, Somesh Jha, Kamalika Chaudhuri:
Analyzing the Robustness of Nearest Neighbors to Adversarial Examples. CoRR abs/1706.03922 (2017) - [i15]Adwait Nadkarni, William Enck, Somesh Jha, Jessica Staddon:
Policy by Example: An Approach for Security Policy Specification. CoRR abs/1707.03967 (2017) - [i14]Tianhao Wang, Ninghui Li, Somesh Jha:
Locally Differentially Private Heavy Hitter Identification. CoRR abs/1708.06674 (2017) - [i13]Samuel Yeom, Matt Fredrikson, Somesh Jha:
The Unintended Consequences of Overfitting: Training Data Inference Attacks. CoRR abs/1709.01604 (2017) - [i12]Irfan Ul Haq, Sergio Chica, Juan Caballero, Somesh Jha:
Malware Lineage in the Wild. CoRR abs/1710.05202 (2017) - [i11]Xi Wu, Uyeong Jang, Lingjiao Chen, Somesh Jha:
Manifold Assumption and Defenses Against Adversarial Perturbations. CoRR abs/1711.08001 (2017) - [i10]Irene Giacomelli, Somesh Jha, C. David Page, Kyonghwan Yoon:
Privacy-Preserving Ridge Regression on Distributed Data. IACR Cryptol. ePrint Arch. 2017: 707 (2017) - [i9]Irene Giacomelli, Somesh Jha, Marc Joye, C. David Page, Kyonghwan Yoon:
Privacy-Preserving Ridge Regression with only Linearly-Homomorphic Encryption. IACR Cryptol. ePrint Arch. 2017: 979 (2017) - 2016
- [j25]Damien Octeau, Daniel Luchaup, Somesh Jha, Patrick D. McDaniel:
Composite Constant Propagation and its Application to Android Program Analysis. IEEE Trans. Software Eng. 42(11): 999-1014 (2016) - [c119]Xi Wu, Matthew Fredrikson, Somesh Jha, Jeffrey F. Naughton:
A Methodology for Formalizing Model-Inversion Attacks. CSF 2016: 355-370 - [c118]Nicolas Papernot, Patrick D. McDaniel, Somesh Jha, Matt Fredrikson, Z. Berkay Celik, Ananthram Swami:
The Limitations of Deep Learning in Adversarial Settings. EuroS&P 2016: 372-387 - [c117]Damien Octeau, Somesh Jha, Matthew L. Dering, Patrick D. McDaniel, Alexandre Bartel, Li Li, Jacques Klein, Yves Le Traon:
Combining static analysis with probabilistic models to enable market-scale Android inter-component analysis. POPL 2016: 469-484 - [c116]Nicolas Papernot, Patrick D. McDaniel, Xi Wu, Somesh Jha, Ananthram Swami:
Distillation as a Defense to Adversarial Perturbations Against Deep Neural Networks. IEEE Symposium on Security and Privacy 2016: 582-597 - [c115]Adwait Nadkarni, Benjamin Andow, William Enck, Somesh Jha:
Practical DIFC Enforcement on Android. USENIX Security Symposium 2016: 1119-1136 - [i8]Nicolas Papernot, Patrick D. McDaniel, Ian J. Goodfellow, Somesh Jha, Z. Berkay Celik, Ananthram Swami:
Practical Black-Box Attacks against Deep Learning Systems using Adversarial Examples. CoRR abs/1602.02697 (2016) - [i7]Vaibhav Rastogi, Drew Davidson, Lorenzo De Carli, Somesh Jha, Patrick D. McDaniel:
Towards Least Privilege Containers with Cimplifier. CoRR abs/1602.08410 (2016) - [i6]Xi Wu, Arun Kumar, Kamalika Chaudhuri, Somesh Jha, Jeffrey F. Naughton:
Differentially Private Stochastic Gradient Descent for in-RDBMS Analytics. CoRR abs/1606.04722 (2016) - 2015
- [c114]Matt Fredrikson, Somesh Jha, Thomas Ristenpart:
Model Inversion Attacks that Exploit Confidence Information and Basic Countermeasures. CCS 2015: 1322-1333 - [c113]Damien Octeau, Daniel Luchaup, Matthew L. Dering, Somesh Jha, Patrick D. McDaniel:
Composite Constant Propagation: Application to Android Inter-Component Communication Analysis. ICSE (1) 2015: 77-88 - [i5]Nicolas Papernot, Patrick D. McDaniel, Xi Wu, Somesh Jha, Ananthram Swami:
Distillation as a Defense to Adversarial Perturbations against Deep Neural Networks. CoRR abs/1511.04508 (2015) - [i4]Nicolas Papernot, Patrick D. McDaniel, Somesh Jha, Matt Fredrikson, Z. Berkay Celik, Ananthram Swami:
The Limitations of Deep Learning in Adversarial Settings. CoRR abs/1511.07528 (2015) - [i3]Xi Wu, Matthew Fredrikson, Wentao Wu, Somesh Jha, Jeffrey F. Naughton:
Revisiting Differentially Private Regression: Lessons From Learning Theory and their Consequences. CoRR abs/1512.06388 (2015) - 2014
- [c112]Daniel Luchaup, Thomas Shrimpton, Thomas Ristenpart, Somesh Jha:
Formatted Encryption Beyond Regular Languages. CCS 2014: 1292-1303 - [c111]Lorenzo De Carli, Robin Sommer, Somesh Jha:
Beyond Pattern Matching: A Concurrency Model for Stateful Deep Packet Inspection. CCS 2014: 1378-1390 - [c110]Matthew Fredrikson, Somesh Jha:
Satisfiability modulo counting: a new approach for analyzing privacy properties. CSL-LICS 2014: 42:1-42:10 - [c109]Daniel Luchaup, Lorenzo De Carli, Somesh Jha, Eric Bach:
Deep packet inspection with DFA-trees and parametrized language overapproximation. INFOCOM 2014: 531-539 - [c108]Richard Joiner, Thomas W. Reps, Somesh Jha, Mohan Dhawan, Vinod Ganapathy:
Efficient runtime-enforcement techniques for policy weaving. SIGSOFT FSE 2014: 224-234 - [c107]Matthew Fredrikson, Eric Lantz, Somesh Jha, Simon M. Lin, David Page, Thomas Ristenpart:
Privacy in Pharmacogenetics: An End-to-End Case Study of Personalized Warfarin Dosing. USENIX Security Symposium 2014: 17-32 - [c106]Daniel Luchaup, Kevin P. Dyer, Somesh Jha, Thomas Ristenpart, Thomas Shrimpton:
LibFTE: A Toolkit for Constructing Practical, Format-Abiding Encryption Schemes. USENIX Security Symposium 2014: 877-891 - 2013
- [j24]Martin Franz, Björn Deiseroth, Kay Hamacher, Somesh Jha, Stefan Katzenbeisser, Heike Schröder:
Secure computations on non-integer values with applications to privacy-preserving sequence analysis. Inf. Secur. Tech. Rep. 17(3): 117-128 (2013) - [c105]William R. Harris, Guoliang Jin, Shan Lu, Somesh Jha:
Validating Library Usage Interactively. CAV 2013: 796-812 - [c104]Florian Sagstetter, Martin Lukasiewycz, Sebastian Steinhorst, Marko Wolf, Alexandre Bouard, William R. Harris, Somesh Jha, Thomas Peyrin, Axel Poschmann, Samarjit Chakraborty:
Security challenges in automotive hardware/software architecture design. DATE 2013: 458-463 - [c103]Somesh Jha, Thomas W. Reps, William R. Harris:
Secure programs via game-based synthesis. FMCAD 2013: 12-13 - [c102]Somesh Jha, Matthew Fredrikson, Mihai Christodorescu, Reiner Sailer, Xifeng Yan:
Synthesizing near-optimal malware specifications from suspicious behaviors. MALWARE 2013: 41-50 - [c101]William R. Harris, Somesh Jha, Thomas W. Reps, Jonathan Anderson, Robert N. M. Watson:
Declarative, Temporal, and Practical Programming with Capabilities. IEEE Symposium on Security and Privacy 2013: 18-32 - [c100]Drew Davidson, Benjamin Moench, Thomas Ristenpart, Somesh Jha:
FIE on Firmware: Finding Vulnerabilities in Embedded Systems Using Symbolic Execution. USENIX Security Symposium 2013: 463-478 - [c99]Damien Octeau, Patrick D. McDaniel, Somesh Jha, Alexandre Bartel, Eric Bodden, Jacques Klein, Yves Le Traon:
Effective Inter-Component Communication Mapping in Android: An Essential Step Towards Holistic Security Analysis. USENIX Security Symposium 2013: 543-558 - 2012
- [j23]Paul F. Syverson, Somesh Jha:
Guest Editorial: Special Issue on Computer and Communications Security. ACM Trans. Inf. Syst. Secur. 15(1): 1:1-1:2 (2012) - [c98]Matthew Fredrikson, Richard Joiner, Somesh Jha, Thomas W. Reps, Phillip A. Porras, Hassen Saïdi, Vinod Yegneswaran:
Efficient Runtime Policy Enforcement Using Counterexample-Guided Abstraction Refinement. CAV 2012: 548-563 - [c97]William R. Harris, Somesh Jha, Thomas W. Reps:
Secure Programming via Visibly Pushdown Safety Games. CAV 2012: 581-598 - [c96]Wenchao Li, Sanjit A. Seshia, Somesh Jha:
CrowdMine: towards crowdsourced human-assisted verification. DAC 2012: 1254-1255 - [c95]Marc de Kruijf, Karthikeyan Sankaralingam, Somesh Jha:
Static analysis and compiler design for idempotent processing. PLDI 2012: 475-486 - [c94]Damien Octeau, Somesh Jha, Patrick D. McDaniel:
Retargeting Android applications to Java bytecode. SIGSOFT FSE 2012: 6 - 2011
- [j22]Daniel Luchaup, Randy Smith, Cristian Estan, Somesh Jha:
Speculative Parallel Pattern Matching. IEEE Trans. Inf. Forensics Secur. 6(2): 438-451 (2011) - [c93]Matthew Fredrikson, Mihai Christodorescu, Somesh Jha:
Dynamic Behavior Matching: A Complexity Analysis and New Approximation Algorithms. CADE 2011: 252-267 - [c92]Martin Franz, Björn Deiseroth, Kay Hamacher, Somesh Jha, Stefan Katzenbeisser, Heike Schröder:
Towards Secure Bioinformatics Services (Short Paper). Financial Cryptography 2011: 276-283 - [p4]Mihai Christodorescu, Matthew Fredrikson, Somesh Jha, Jonathon T. Giffin:
End-to-End Software Diversification of Internet Services. Moving Target Defense 2011: 117-130 - 2010
- [b1]Anupam Datta, Somesh Jha, Ninghui Li, David Melski, Thomas W. Reps:
Analysis Techniques for Information Security. Synthesis Lectures on Information Security, Privacy, and Trust, Morgan & Claypool Publishers 2010, ISBN 978-3-031-01206-8 - [j21]Somesh Jha, Stefan Katzenbeisser, Christian Schallhart, Helmut Veith, Stephen Chenney:
Semantic integrity in large-scale online simulations. ACM Trans. Internet Techn. 10(1): 2:1-2:24 (2010) - [c91]Amit Kumar, Lorenzo De Carli, Sung Jin Kim, Marc de Kruijf, Karthikeyan Sankaralingam, Cristian Estan, Somesh Jha:
Design and implementation of the PLUG architecture for programmable and efficient network lookups. PACT 2010: 331-342 - [c90]Somesh Jha:
Retrofitting Legacy Code for Security. CAV 2010: 19 - [c89]William R. Harris, Somesh Jha, Thomas W. Reps:
DIFC programs by automatic instrumentation. CCS 2010: 284-296 - [c88]Dave King, Susmit Jha, Divya Muthukumaran, Trent Jaeger, Somesh Jha, Sanjit A. Seshia:
Automating Security Mediation Placement. ESOP 2010: 327-344 - [c87]Matt Fredrikson, Somesh Jha, Mihai Christodorescu, Reiner Sailer, Xifeng Yan:
Synthesizing Near-Optimal Malware Specifications from Suspicious Behaviors. IEEE Symposium on Security and Privacy 2010: 45-60 - [c86]Roberto Paleari, Lorenzo Martignoni, Emanuele Passerini, Drew Davidson, Matt Fredrikson, Jonathon T. Giffin, Somesh Jha:
Automatic Generation of Remediation Procedures for Malware Infections. USENIX Security Symposium 2010: 419-434 - [c85]Martin Franz, Björn Deiseroth, Kay Hamacher, Somesh Jha, Stefan Katzenbeisser, Heike Schröder:
Secure computations on non-integer values. WIFS 2010: 1-6 - [p3]Paul Barford, Marc Dacier, Thomas G. Dietterich, Matt Fredrikson, Jonathon T. Giffin, Sushil Jajodia, Somesh Jha, Jason H. Li, Peng Liu, Peng Ning, Xinming Ou, Dawn Song, Laura Strater, Vipin Swarup, George P. Tadda, C. Wang, John Yen:
Cyber SA: Situational Awareness for Cyber Defense. Cyber Situational Awareness 2010: 3-13 - [p2]Matt Fredrikson, Mihai Christodorescu, Jonathon T. Giffin, Somesh Jha:
A Declarative Framework for Intrusion Analysis. Cyber Situational Awareness 2010: 179-200 - [e6]Somesh Jha, Anish Mathuria:
Information Systems Security - 6th International Conference, ICISS 2010, Gandhinagar, India, December 17-19, 2010. Proceedings. Lecture Notes in Computer Science 6503, Springer 2010, ISBN 978-3-642-17713-2 [contents] - [e5]Somesh Jha, Robin Sommer, Christian Kreibich:
Recent Advances in Intrusion Detection, 13th International Symposium, RAID 2010, Ottawa, Ontario, Canada, September 15-17, 2010. Proceedings. Lecture Notes in Computer Science 6307, Springer 2010, ISBN 978-3-642-15511-6 [contents] - [i2]Martin Franz, Björn Deiseroth, Kay Hamacher, Somesh Jha, Stefan Katzenbeisser, Heike Schröder:
Secure Computations on Non-Integer Values. IACR Cryptol. ePrint Arch. 2010: 499 (2010)
2000 – 2009
- 2009
- [c84]Drew Davidson, Randy Smith, Nic Doyle, Somesh Jha:
Protocol Normalization Using Attribute Grammars. ESORICS 2009: 216-231 - [c83]William R. Harris, Nicholas Kidd, Sagar Chaki, Somesh Jha, Thomas W. Reps:
Verifying Information Flow Control over Unbounded Processes. FM 2009: 773-789 - [c82]Daniel Luchaup, Randy Smith, Cristian Estan, Somesh Jha:
Multi-byte Regular Expression Matching with Speculation. RAID 2009: 284-303 - [e4]Ehab Al-Shaer, Somesh Jha, Angelos D. Keromytis:
Proceedings of the 2009 ACM Conference on Computer and Communications Security, CCS 2009, Chicago, Illinois, USA, November 9-13, 2009. ACM 2009, ISBN 978-1-60558-894-0 [contents] - [e3]Engin Kirda, Somesh Jha, Davide Balzarotti:
Recent Advances in Intrusion Detection, 12th International Symposium, RAID 2009, Saint-Malo, France, September 23-25, 2009. Proceedings. Lecture Notes in Computer Science 5758, Springer 2009, ISBN 978-3-642-04341-3 [contents] - 2008
- [j20]David Brumley, James Newsome, Dawn Song, Hao Wang, Somesh Jha:
Theory and Techniques for Automatic Generation of Vulnerability-Based Signatures. IEEE Trans. Dependable Secur. Comput. 5(4): 224-241 (2008) - [j19]Somesh Jha, Ninghui Li, Mahesh V. Tripunitara, Qihua Wang, William H. Winsborough:
Towards Formal Verification of Role-Based Access Control Policies. IEEE Trans. Dependable Secur. Comput. 5(4): 242-255 (2008) - [j18]Mila Dalla Preda, Mihai Christodorescu, Somesh Jha, Saumya K. Debray:
A semantics-based approach to malware detection. ACM Trans. Program. Lang. Syst. 30(5): 25:1-25:54 (2008) - [c81]Vinod Ganapathy, Matthew J. Renzelmann, Arini Balakrishnan, Michael M. Swift, Somesh Jha:
The design and implementation of microdrivers. ASPLOS 2008: 168-178 - [c80]Randy Smith, Cristian Estan, Somesh Jha, Ida Sri Rejeki Siahaan:
Fast Signature Matching Using Extended Finite Automaton (XFA). ICISS 2008: 158-172 - [c79]Mihai Christodorescu, Somesh Jha, Christopher Kruegel:
Mining specifications of malicious behavior. ISEC 2008: 5-14 - [c78]Lorenzo Martignoni, Elizabeth Stinson, Matt Fredrikson, Somesh Jha, John C. Mitchell:
A Layered Architecture for Detecting Malicious Behaviors. RAID 2008: 78-97 - [c77]Randy Smith, Cristian Estan, Somesh Jha, Shijin Kong:
Deflating the big bang: fast and scalable deep packet inspection with extended finite automata. SIGCOMM 2008: 207-218 - [c76]Dave King, Trent Jaeger, Somesh Jha, Sanjit A. Seshia:
Effective blame for information-flow violations. SIGSOFT FSE 2008: 250-260 - [c75]Randy Smith, Cristian Estan, Somesh Jha:
XFA: Faster Signature Matching with Extended Automata. SP 2008: 187-201 - [c74]Somesh Jha, Louis Kruger, Vitaly Shmatikov:
Towards Practical Privacy for Genomic Computation. SP 2008: 216-230 - [e2]Peng Ning, Paul F. Syverson, Somesh Jha:
Proceedings of the 2008 ACM Conference on Computer and Communications Security, CCS 2008, Alexandria, Virginia, USA, October 27-31, 2008. ACM 2008, ISBN 978-1-59593-810-7 [contents] - 2007
- [j17]Mihai Christodorescu, Somesh Jha, Johannes Kinder, Stefan Katzenbeisser, Helmut Veith:
Software transformations to improve malware detection. J. Comput. Virol. 3(4): 253-265 (2007) - [c73]Lorenzo Martignoni, Mihai Christodorescu, Somesh Jha:
OmniUnpack: Fast, Generic, and Safe Unpacking of Malware. ACSAC 2007: 431-441 - [c72]David Brumley, Hao Wang, Somesh Jha, Dawn Xiaodong Song:
Creating Vulnerability Signatures Using Weakest Preconditions. CSF 2007: 311-325 - [c71]Vinod Ganapathy, Arini Balakrishnan, Michael M. Swift, Somesh Jha:
Microdrivers: A New Architecture for Device Drivers. HotOS 2007 - [c70]Vinod Ganapathy, Dave King, Trent Jaeger, Somesh Jha:
Mining Security-Sensitive Operations in Legacy Code Using Concept Analysis. ICSE 2007: 458-467 - [c69]Mila Dalla Preda, Mihai Christodorescu, Somesh Jha, Saumya K. Debray:
A semantics-based approach to malware detection. POPL 2007: 377-388 - [c68]Mihai Christodorescu, Somesh Jha, Christopher Kruegel:
Mining specifications of malicious behavior. ESEC/SIGSOFT FSE 2007: 5-14 - [c67]Somesh Jha, Stefan Katzenbeisser, Christian Schallhart, Helmut Veith, Stephen Chenney:
Enforcing Semantic Integrity on Untrusted Clients in Networked Virtual Environments. S&P 2007: 179-186 - [e1]Mihai Christodorescu, Somesh Jha, Douglas Maughan, Dawn Song, Cliff Wang:
Malware Detection. Advances in Information Security 27, Springer 2007, ISBN 978-0-387-32720-4 [contents] - [i1]Somesh Jha, Stefan Katzenbeisser, Christian Schallhart, Helmut Veith, Stephen Chenney:
Enforcing Semantic Integrity on Untrusted Clients in Networked Virtual Environments. IACR Cryptol. ePrint Arch. 2007: 56 (2007) - 2006
- [c66]Randy Smith, Cristian Estan, Somesh Jha:
Backtracking Algorithmic Complexity Attacks against a NIDS. ACSAC 2006: 89-98 - [c65]Hao Wang, Somesh Jha, Vinod Ganapathy:
NetSpy: Automatic Generation of Spyware Signatures for NIDS. ACSAC 2006: 99-108 - [c64]Shai Rubin, Somesh Jha, Barton P. Miller:
Protomatching network traffic for high throughputnetwork intrusion detection. CCS 2006: 47-58 - [c63]Louis Kruger, Somesh Jha, Eu-Jin Goh, Dan Boneh:
Secure function evaluation with ordered binary decision diagrams. CCS 2006: 410-420 - [c62]Shai Rubin, Somesh Jha, Barton P. Miller:
On the Completeness of Attack Mutation Algorithms. CSFW 2006: 43-56 - [c61]Hao Wang, Somesh Jha, Thomas W. Reps, Stefan Schwoon, Stuart G. Stubblebine:
Reducing the Dependence of SPKI/SDSI on PKI. ESORICS 2006: 156-173 - [c60]Jonathon T. Giffin, Somesh Jha, Barton P. Miller:
Automated Discovery of Mimicry Attacks. RAID 2006: 41-60 - [c59]David Brumley, James Newsome, Dawn Xiaodong Song, Hao Wang, Somesh Jha:
Towards Automatic Generation of Vulnerability-Based Signatures. S&P 2006: 2-16 - [c58]Vinod Ganapathy, Trent Jaeger, Somesh Jha:
Retrofitting Legacy Code for Authorization Policy Enforcement. S&P 2006: 214-229 - [c57]Somesh Jha, Stefan Schwoon, Hao Wang, Thomas W. Reps:
Weighted Pushdown Systems and Trust-Management Systems. TACAS 2006: 1-26 - 2005
- [j16]Sagar Chaki, Edmund M. Clarke, Somesh Jha, Helmut Veith:
An Iterative Framework for Simulation Conformance. J. Log. Comput. 15(4): 465-488 (2005) - [j15]Thomas W. Reps, Stefan Schwoon, Somesh Jha, David Melski:
Weighted pushdown systems and their application to interprocedural dataflow analysis. Sci. Comput. Program. 58(1-2): 206-263 (2005) - [c56]Vinod Ganapathy, Trent Jaeger, Somesh Jha:
Automatic placement of authorization hooks in the linux security modules framework. CCS 2005: 330-339 - [c55]Somesh Jha, Louis Kruger, Patrick D. McDaniel:
Privacy Preserving Clustering. ESORICS 2005: 397-417 - [c54]Muthian Sivathanu, Andrea C. Arpaci-Dusseau, Remzi H. Arpaci-Dusseau, Somesh Jha:
A Logic of File Systems. FAST 2005 - [c53]Vinod Ganapathy, Sanjit A. Seshia, Somesh Jha, Thomas W. Reps, Randal E. Bryant:
Automatic discovery of API-level exploits. ICSE 2005: 312-321 - [c52]Jonathon T. Giffin, David Dagon, Somesh Jha, Wenke Lee, Barton P. Miller:
Environment-Sensitive Intrusion Detection. RAID 2005: 185-206 - [c51]Shai Rubin, Somesh Jha, Barton P. Miller:
Language-Based Generation and Evaluation of NIDS Signatures. S&P 2005: 3-17 - [c50]Mihai Christodorescu, Somesh Jha, Sanjit A. Seshia, Dawn Xiaodong Song, Randal E. Bryant:
Semantics-Aware Malware Detection. S&P 2005: 32-46 - [c49]Vinod Yegneswaran, Jonathon T. Giffin, Paul Barford, Somesh Jha:
An Architecture for Generating Semantic Aware Signatures. USENIX Security Symposium 2005 - 2004
- [j14]Somesh Jha, Thomas W. Reps:
Model checking SPKI/SDSI. J. Comput. Secur. 12(3-4): 317-353 (2004) - [j13]Sagar Chaki, Edmund M. Clarke, Alex Groce, Somesh Jha, Helmut Veith:
Modular Verification of Software Components in C. IEEE Trans. Software Eng. 30(6): 388-402 (2004) - [c48]Shai Rubin, Somesh Jha, Barton P. Miller:
Automatic Generation and Analysis of NIDS Attacks. ACSAC 2004: 28-38 - [c47]Mihai Christodorescu, Somesh Jha:
Testing malware detectors. ISSTA 2004: 34-44 - [c46]Jonathon T. Giffin, Somesh Jha, Barton P. Miller:
Efficient Context-Sensitive Intrusion Detection. NDSS 2004 - [c45]Vinod Yegneswaran, Paul Barford, Somesh Jha:
Global Intrusion Detection in the DOMINO Overlay System. NDSS 2004 - [c44]Hao Wang, Somesh Jha, Miron Livny, Patrick D. McDaniel:
Security Policy Reconciliation in Distributed Computing Environments. POLICY 2004: 137- - [c43]Henry Hanping Feng, Jonathon T. Giffin, Yong Huang, Somesh Jha, Wenke Lee, Barton P. Miller:
Formalizing Sensitivity in Static Analysis for Intrusion Detection. S&P 2004: 194- - 2003
- [j12]Edmund M. Clarke, Orna Grumberg, Somesh Jha, Yuan Lu, Helmut Veith:
Counterexample-guided abstraction refinement for symbolic model checking. J. ACM 50(5): 752-794 (2003) - [j11]Edmund M. Clarke, Somesh Jha, Wilfredo R. Marrero:
Efficient verification of security protocols using partial-order reductions. Int. J. Softw. Tools Technol. Transf. 4(2): 173-188 (2003) - [c42]Vinod Ganapathy, Somesh Jha, David Chandler, David Melski, David Vitek:
Buffer overrun detection using linear programming and static analysis. CCS 2003: 345-354 - [c41]Stefan Schwoon, Somesh Jha, Thomas W. Reps, Stuart G. Stubblebine:
On Generalized Authorization Problems. CSFW 2003: 202- - [c40]Sagar Chaki, Edmund M. Clarke, Alex Groce, Somesh Jha, Helmut Veith:
Modular Verification of Software Components in C. ICSE 2003: 385-395 - [c39]Thomas W. Reps, Stefan Schwoon, Somesh Jha:
Weighted Pushdown Systems and Their Application to Interprocedural Dataflow Analysis. SAS 2003: 189-213 - [c38]Sagar Chaki, Pascal Fenkam, Harald C. Gall, Somesh Jha, Engin Kirda, Helmut Veith:
Integrating Publish/Subscribe into a Mobile Teamwork Support Platform. SEKE 2003: 510-517 - [c37]Mihai Christodorescu, Somesh Jha:
Static Analysis of Executables to Detect Malicious Patterns. USENIX Security Symposium 2003 - 2002
- [c36]Somesh Jha, Oleg Sheyner, Jeannette M. Wing:
Two Formal Analys s of Attack Graphs. CSFW 2002: 49-63 - [c35]Somesh Jha, Thomas W. Reps:
Analysis of SPKI/SDSI Certificates Using Model Checking. CSFW 2002: 129- - [c34]Somesh Jha, Jens Palsberg, Tian Zhao:
Efficient Type Matching. FoSSaCS 2002: 187-204 - [c33]Edmund M. Clarke, Somesh Jha, Yuan Lu, Helmut Veith:
Tree-Like Counterexamples in Model Checking. LICS 2002: 19-29 - [c32]Oleg Sheyner, Joshua W. Haines, Somesh Jha, Richard Lippmann, Jeannette M. Wing:
Automated Generation and Analysis of Attack Graphs. S&P 2002: 273-284 - [c31]Jonathon T. Giffin, Somesh Jha, Barton P. Miller:
Detecting Manipulated Remote Call Streams. USENIX Security Symposium 2002: 61-79 - 2001
- [c30]Pankaj Chauhan, Edmund M. Clarke, Somesh Jha, James H. Kukula, Helmut Veith, Dong Wang:
Using Combinatorial Optimization Methods for Quantification Scheduling. CHARME 2001: 293-309 - [c29]Somesh Jha, Kymie M. C. Tan, Roy A. Maxion:
Markov Chains, Classifiers, and Intrusion Detection. CSFW 2001: 206-219 - [c28]Edmund M. Clarke, Orna Grumberg, Somesh Jha, Yuan Lu, Helmut Veith:
Progress on the State Explosion Problem in Model Checking. Informatics 2001: 176-194 - [c27]Pankaj Chauhan, Edmund M. Clarke, Somesh Jha, James H. Kukula, Thomas R. Shiple, Helmut Veith, Dong Wang:
Non-linear Quantification Scheduling in Image Computation. ICCAD 2001: 293- - [c26]Somesh Jha, Jeannette M. Wing:
Survivability Analysis of Network Systems. ICSE 2001: 307-317 - [c25]Alexis Campailla, Sagar Chaki, Edmund M. Clarke, Somesh Jha, Helmut Veith:
Efficient Filtering in Publish-Subscribe Systems Using Binary Decision. ICSE 2001: 443-452 - 2000
- [j10]Edmund M. Clarke, Somesh Jha, Wilfredo R. Marrero:
Verifying security protocols with Brutus. ACM Trans. Softw. Eng. Methodol. 9(4): 443-487 (2000) - [c24]Sergey Berezin, Edmund M. Clarke, Somesh Jha, Will Marrero:
Model checking algorithms for the µ-calculus. Proof, Language, and Interaction 2000: 309-338 - [c23]Edmund M. Clarke, Orna Grumberg, Somesh Jha, Yuan Lu, Helmut Veith:
Counterexample-Guided Abstraction Refinement. CAV 2000: 154-169 - [c22]Somesh Jha, Jeannette M. Wing, Richard C. Linger, Thomas A. Longstaff:
Survivability Analysis of Network Specifications. DSN 2000: 613-622 - [c21]Edmund M. Clarke, Somesh Jha, Wilfredo R. Marrero:
Partial Order Reductions for Security Protocol Verification. TACAS 2000: 503-518
1990 – 1999
- 1999
- [j9]Prasad Chalasani, Somesh Jha, Isaac Saias:
Approximate Option Pricing. Algorithmica 25(1): 2-21 (1999) - [c20]Edmund M. Clarke, Somesh Jha, Yuan Lu, Dong Wang:
Abstract BDDs: A Technique for Using Abstraction in Model Checking. CHARME 1999: 172-186 - [c19]Somesh Jha, Doron A. Peled:
Generalized Stuttering Equivalence. PDPTA 1999: 1054-1060 - 1998
- [j8]Onn Shehory, Katia P. Sycara, Prasad Chalasani, Somesh Jha:
Agent cloning: an approach to agent mobility and resource allocation. IEEE Commun. Mag. 36(7): 58 (1998) - [j7]Jürgen Dingel, David Garlan, Somesh Jha, David Notkin:
Towards a Formal Treatment of Implicit Invocation Using Rely/Guarantee Reasoning. Formal Aspects Comput. 10(3): 193-213 (1998) - [j6]Daniel Jackson, Somesh Jha, Craig Damon:
Isomorph-Free Model Enumeration: A New Method for Checking Relational Specifications. ACM Trans. Program. Lang. Syst. 20(2): 302-343 (1998) - [c18]Prasad Chalasani, Somesh Jha, Onn Shehory, Katia P. Sycara:
Query Restart Strategies for Web Agent. Agents 1998: 124-131 - [c17]Somesh Jha, Prasad Chalasani, Onn Shehory, Katia P. Sycara:
A Formal Treatment of Distributed Matchmaking. Agents 1998: 457-458 - [c16]Onn Shehory, Katia P. Sycara, Prasad Chalasani, Somesh Jha:
Increasing Resource Utilization and Task Performance by Agent Cloning. ATAL 1998: 413-426 - [c15]Edmund M. Clarke, E. Allen Emerson, Somesh Jha, A. Prasad Sistla:
Symmetry Reductions in Model Checking. CAV 1998: 147-158 - [c14]Prasad Chalasani, Somesh Jha, Onn Shehory, Katia P. Sycara:
Strategies for Querying Information Agents. CIA 1998: 94-107 - [c13]Onn Shehory, Katia P. Sycara, Prasad Chalasani, Somesh Jha:
Agent Cloning. ICMAS 1998: 463-464 - [c12]Edmund M. Clarke, Somesh Jha, Wilfredo R. Marrero:
Using state space exploration and a natural deduction style message derivation engine to verify security protocols. PROCOMET 1998: 87-106 - [c11]David Garlan, Somesh Jha, David Notkin:
Reasoning about Implicit Invocation. SIGSOFT FSE 1998: 209-221 - 1997
- [j5]Anca Browne, Edmund M. Clarke, Somesh Jha, David E. Long, Wilfredo R. Marrero:
An Improved Algorithm for the Evaluation of Fixpoint Expressions. Theor. Comput. Sci. 178(1-2): 237-255 (1997) - [j4]Edmund M. Clarke, Orna Grumberg, Somesh Jha:
Verifying Parameterized Networks. ACM Trans. Program. Lang. Syst. 19(5): 726-750 (1997) - [c10]Onn Shehory, Katia P. Sycara, Somesh Jha:
Multi-Agent Coordination through Coalition Formation. ATAL 1997: 143-154 - [c9]Somesh Jha, Yuan Lu, Marius Minea, Edmund M. Clarke:
Equivalence Checking Using Abstract BDDs. ICCD 1997: 332-337 - [c8]E. Allen Emerson, Somesh Jha, Doron A. Peled:
Combining Partial Order and Symmetry Reductions. TACAS 1997: 19-34 - 1996
- [j3]Edmund M. Clarke, Somesh Jha, Reinhard Enders, Thomas Filkorn:
Exploiting Symmetry in Temporal Logic Model Checking. Formal Methods Syst. Des. 9(1/2): 77-104 (1996) - [c7]Prasad Chalasani, Somesh Jha, Isaac Saias:
Approximate Option Pricing. FOCS 1996: 244-253 - [c6]Daniel Jackson, Somesh Jha, Craig Damon:
Faster Checking of Software Specifications by Eliminating Isomorphs. POPL 1996: 79-90 - [c5]Craig Damon, Daniel Jackson, Somesh Jha:
Checking Relational Specifications With Binary Decision Diagrams. SIGSOFT FSE 1996: 70-80 - 1995
- [j2]Edmund M. Clarke, Orna Grumberg, Hiromi Hiraishi, Somesh Jha, David E. Long, Kenneth L. McMillan, Linda A. Ness:
Verification of the Futurebus+ Cache Coherence Protocol. Formal Methods Syst. Des. 6(2): 217-232 (1995) - [c4]Edmund M. Clarke, Orna Grumberg, Somesh Jha:
Veryfying Parameterized Networks using Abstraction and Regular Languages. CONCUR 1995: 395-407 - [p1]Edmund M. Clarke, Somesh Jha:
Symmetry and Induction in Model Checking. Computer Science Today 1995: 455-470 - 1994
- [c3]David E. Long, Anca Browne, Edmund M. Clarke, Somesh Jha, Wilfredo R. Marrero:
An Improved Algorithm for the Evaluation of Fixpoint Expressions. CAV 1994: 338-350 - 1993
- [c2]Edmund M. Clarke, Thomas Filkorn, Somesh Jha:
Exploiting Symmetry In Temporal Logic Model Checking. CAV 1993: 450-462 - [c1]Edmund M. Clarke, Orna Grumberg, Hiromi Hiraishi, Somesh Jha, David E. Long, Kenneth L. McMillan, Linda A. Ness:
Verification of the Futurebus+ Cache Coherence Protocol. CHDL 1993: 15-30 - 1992
- [j1]Panos M. Pardalos, Somesh Jha:
Complexity of uniqueness and local search in quadratic 0-1 programming. Oper. Res. Lett. 11(2): 119-123 (1992)
Coauthor Index
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