Matt Fredrikson

Publication Activity (10 Years)

Years Active: 2008-2024
Publications (10 Years): 76

Top Topics

Graceful Degradation

Countermeasures

Machine Learning

Linear Regression Models

Top Venues

Publications

Han Zhang, Zifan Wang, Mihir Dhamankar, Matt Fredrikson, Yuvraj Agarwal
VeriSplit: Secure and Practical Offloading of Machine Learning Inferences across IoT Devices. CoRR (2024)
Kai Hu, Weichen Yu, Tianjun Yao, Xiang Li, Wenhe Liu, Lijun Yu, Yining Li, Kai Chen, Zhiqiang Shen, Matt Fredrikson
Efficient LLM Jailbreak via Adaptive Dense-to-sparse Constrained Optimization. CoRR (2024)
Weiran Lin, Anna Gerchanovsky, Omer Akgul, Lujo Bauer, Matt Fredrikson, Zifan Wang
Sales Whisperer: A Human-Inconspicuous Attack on LLM Brand Recommendations. CoRR (2024)
Andy Zou, Long Phan, Justin Wang, Derek Duenas, Maxwell Lin, Maksym Andriushchenko, Rowan Wang, Zico Kolter, Matt Fredrikson, Dan Hendrycks
Improving Alignment and Robustness with Circuit Breakers. CoRR (2024)
Kai Hu, Klas Leino, Zifan Wang, Matt Fredrikson
A Recipe for Improved Certifiable Robustness. ICLR (2024)
Kai Hu, Andy Zou, Zifan Wang, Klas Leino, Matt Fredrikson
Unlocking Deterministic Robustness Certification on ImageNet. NeurIPS (2023)
Andy Zou, Zifan Wang, J. Zico Kolter, Matt Fredrikson
Universal and Transferable Adversarial Attacks on Aligned Language Models. CoRR (2023)
Kai Hu, Klas Leino, Zifan Wang, Matt Fredrikson
A Recipe for Improved Certifiable Robustness: Capacity and Data. CoRR (2023)
Chi Zhang, Zifan Wang, Ravi Mangal, Matt Fredrikson, Limin Jia, Corina S. Pasareanu
Transfer Attacks and Defenses for Large Language Models on Coding Tasks. CoRR (2023)
Ravi Mangal, Klas Leino, Zifan Wang, Kai Hu, Weicheng Yu, Corina S. Pasareanu, Anupam Datta, Matt Fredrikson
Robustness Still Worthwhile? CoRR (2023)
Kai Hu, Andy Zou, Zifan Wang, Klas Leino, Matt Fredrikson
Scaling in Depth: Unlocking Robustness Certification on ImageNet. CoRR (2023)
Andy Zou, Long Phan, Sarah Chen, James Campbell, Phillip Guo, Richard Ren, Alexander Pan, Xuwang Yin, Mantas Mazeika, Ann-Kathrin Dombrowski, Shashwat Goel, Nathaniel Li, Michael J. Byun, Zifan Wang, Alex Mallen, Steven Basart, Sanmi Koyejo, Dawn Song, Matt Fredrikson, J. Zico Kolter, Dan Hendrycks
Representation Engineering: A Top-Down Approach to AI Transparency. CoRR (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)
Ravi Mangal, Zifan Wang, Chi Zhang, Klas Leino, Corina S. Pasareanu, Matt Fredrikson
On the Perils of Cascading Robust Classifiers. ICLR (2023)
Zifan Wang, Matt Fredrikson, Anupam Datta
Robust Models Are More Interpretable Because Attributions Look Normal. ICML (2022)
Daniel Gibert, Matt Fredrikson, Carles Mateu, Jordi Planes, Quan Le
Enhancing the insertion of NOP instructions to obfuscate malware via deep reinforcement learning. Comput. Secur. 113 (2022)
Klas Leino, Aymeric Fromherz, Ravi Mangal, Matt Fredrikson, Bryan Parno, Corina S. Pasareanu
Self-correcting Neural Networks for Safe Classification. NSV/FoMLAS@CAV (2022)
Han Zhang, Yuvraj Agarwal, Matt Fredrikson
Protecting user data through ephemeral ownership of IoT devices. MobiSys (2022)
Zifan Wang, Yuhang Yao, Chaoran Zhang, Han Zhang, Youjie Kang, Carlee Joe-Wong, Matt Fredrikson, Anupam Datta
Faithful Explanations for Deep Graph Models. CoRR (2022)
Han Zhang, Yuvraj Agarwal, Matt Fredrikson
TEO: ephemeral ownership for IoT devices to provide granular data control. MobiSys (2022)
Helena Montenegro, Wilson Silva, Alex Gaudio, Matt Fredrikson, Asim Smailagic, Jaime S. Cardoso
Privacy-Preserving Case-Based Explanations: Enabling Visual Interpretability by Protecting Privacy. IEEE Access 10 (2022)
Klas Leino, Chi Zhang, Ravi Mangal, Matt Fredrikson, Bryan Parno, Corina S. Pasareanu
Degradation Attacks on Certifiably Robust Neural Networks. Trans. Mach. Learn. Res. 2022 (2022)
Ravi Mangal, Zifan Wang, Chi Zhang, Klas Leino, Corina S. Pasareanu, Matt Fredrikson
On the Perils of Cascading Robust Classifiers. CoRR (2022)
Marc Juárez, Samuel Yeom, Matt Fredrikson
Black-Box Audits for Group Distribution Shifts. CoRR (2022)
Emily Black, Klas Leino, Matt Fredrikson
Selective Ensembles for Consistent Predictions. ICLR (2022)
Emily Black, Zifan Wang, Matt Fredrikson
Consistent Counterfactuals for Deep Models. ICLR (2022)
Zifan Wang, Matt Fredrikson, Anupam Datta
Boundary Attributions Provide Normal (Vector) Explanations. CoRR (2021)
Emily Black, Klas Leino, Matt Fredrikson
Selective Ensembles for Consistent Predictions. CoRR (2021)
Klas Leino, Aymeric Fromherz, Ravi Mangal, Matt Fredrikson, Bryan Parno, Corina S. Pasareanu
Self-Repairing Neural Networks: Provable Safety for Deep Networks via Dynamic Repair. CoRR (2021)
Anupam Datta, Matt Fredrikson, Klas Leino, Kaiji Lu, Shayak Sen, Ricardo Shih, Zifan Wang
Exploring Conceptual Soundness with TruLens. NeurIPS (Competition and Demos) (2021)
Klas Leino, Zifan Wang, Matt Fredrikson
Globally-Robust Neural Networks. ICML (2021)
Emily Black, Matt Fredrikson
Leave-one-out Unfairness. FAccT (2021)
Daniel Gibert, Matt Fredrikson, Carles Mateu, Jordi Planes, Quan Le
Enhancing the Insertion of NOP Instructions to Obfuscate Malware via Deep Reinforcement Learning. CoRR (2021)
Aymeric Fromherz, Klas Leino, Matt Fredrikson, Bryan Parno, Corina S. Pasareanu
Fast Geometric Projections for Local Robustness Certification. ICLR (2021)
Klas Leino, Matt Fredrikson
Relaxing Local Robustness. CoRR (2021)
Anupam Datta, Matt Fredrikson, Klas Leino, Kaiji Lu, Shayak Sen, Zifan Wang
Machine Learning Explainability and Robustness: Connected at the Hip. KDD (2021)
Emily Black, Matt Fredrikson
Leave-one-out Unfairness. CoRR (2021)
Jason I. Hong, Yuvraj Agarwal, Matt Fredrikson, Mike Czapik, Shawn Hanna, Swarup Sahoo, Judy Chun, Won-Woo Chung, Aniruddh Iyer, Ally Liu, Shen Lu, Rituparna Roychoudhury, Qian Wang, Shan Wang, Siqi Wang, Vida Zhang, Jessica Zhao, Yuan Jiang, Haojian Jin, Sam Kim, Evelyn Kuo, Tianshi Li, Jinping Liu, Yile Liu, Robert Zhang
The Design of the User Interfaces for Privacy Enhancements for Android. CoRR (2021)
Klas Leino, Zifan Wang, Matt Fredrikson
Globally-Robust Neural Networks. CoRR (2021)
Han Zhang, Chi Zhang, Arthur Azevedo de Amorim, Yuvraj Agarwal, Matt Fredrikson, Limin Jia
Netter: Probabilistic, Stateful Network Models. VMCAI (2021)
Emily Black, Zifan Wang, Matt Fredrikson, Anupam Datta
Consistent Counterfactuals for Deep Models. CoRR (2021)
Han Zhang, Abhijith Anilkumar, Matt Fredrikson, Yuvraj Agarwal
Capture: Centralized Library Management for Heterogeneous IoT Devices. USENIX Security Symposium (2021)
Klas Leino, Matt Fredrikson
Relaxing Local Robustness. NeurIPS (2021)
Abhishek Bichhawat, Matt Fredrikson, Jean Yang
Automating Audit with Policy Inference. CSF (2021)
Klas Leino, Matt Fredrikson
Stolen Memories: Leveraging Model Memorization for Calibrated White-Box Membership Inference. USENIX Security Symposium (2020)
Abhishek Bichhawat, Matt Fredrikson, Jean Yang, Akash Trehan
Contextual and Granular Policy Enforcement in Database-backed Applications. AsiaCCS (2020)
Samuel Yeom, Matt Fredrikson
Individual Fairness Revisited: Transferring Techniques from Adversarial Robustness. CoRR (2020)
Kaiji Lu, Piotr Mardziel, Klas Leino, Matt Fredrikson, Anupam Datta
Influence Paths for Characterizing Subject-Verb Number Agreement in LSTM Language Models. ACL (2020)
Zifan Wang, Piotr Mardziel, Anupam Datta, Matt Fredrikson
Interpreting Interpretations: Organizing Attribution Methods by Criteria. CoRR (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)
Zifan Wang, Haofan Wang, Shakul Ramkumar, Matt Fredrikson, Piotr Mardziel, Anupam Datta
Smoothed Geometry for Robust Attribution. CoRR (2020)
Samuel Yeom, Matt Fredrikson
Individual Fairness Revisited: Transferring Techniques from Adversarial Robustness. IJCAI (2020)
Kaiji Lu, Piotr Mardziel, Klas Leino, Matt Fredrikson, Anupam Datta
Influence Paths for Characterizing Subject-Verb Number Agreement in LSTM Language Models. CoRR (2020)
Emily Black, Samuel Yeom, Matt Fredrikson
FlipTest: fairness testing via optimal transport. FAT* (2020)
Zifan Wang, Piotr Mardziel, Anupam Datta, Matt Fredrikson
Interpreting Interpretations: Organizing Attribution Methods by Criteria. CVPR Workshops (2020)
Zilong Tan, Samuel Yeom, Matt Fredrikson, Ameet Talwalkar
Learning Fair Representations for Kernel Models. AISTATS (2020)
Zifan Wang, Haofan Wang, Shakul Ramkumar, Piotr Mardziel, Matt Fredrikson, Anupam Datta
Smoothed Geometry for Robust Attribution. NeurIPS (2020)
Arthur Azevedo de Amorim, Matt Fredrikson, Limin Jia
Reconciling noninterference and gradual typing. LICS (2020)
Aymeric Fromherz, Klas Leino, Matt Fredrikson, Bryan Parno, Corina S. Pasareanu
Fast Geometric Projections for Local Robustness Certification. CoRR (2020)
Emily Black, Samuel Yeom, Matt Fredrikson
FlipTest: Fairness Auditing via Optimal Transport. CoRR (2019)
Zilong Tan, Samuel Yeom, Matt Fredrikson, Ameet Talwalkar
Learning Fair Representations for Kernel Models. CoRR (2019)
Klas Leino, Emily Black, Matt Fredrikson, Shayak Sen, Anupam Datta
Feature-Wise Bias Amplification. ICLR (Poster) (2019)
Klas Leino, Matt Fredrikson
Stolen Memories: Leveraging Model Memorization for Calibrated White-Box Membership Inference. CoRR (2019)
Klas Leino, Shayak Sen, Anupam Datta, Matt Fredrikson, Linyi Li
Influence-Directed Explanations for Deep Convolutional Networks. ITC (2018)
Samuel Yeom, Irene Giacomelli, Matt Fredrikson, Somesh Jha
Privacy Risk in Machine Learning: Analyzing the Connection to Overfitting. CSF (2018)
Ryan Wagner, David Garlan, Matt Fredrikson
Quantitative underpinnings of secure, graceful degradation: poster. HotSoS (2018)
Klas Leino, Matt Fredrikson, Emily Black, Shayak Sen, Anupam Datta
Feature-Wise Bias Amplification. CoRR (2018)
Samuel Yeom, Anupam Datta, Matt Fredrikson
Hunting for Discriminatory Proxies in Linear Regression Models. CoRR (2018)
Abhishek Bichhawat, Akash Trehan, Jean Yang, Matt Fredrikson
ESTRELA: Automated Policy Enforcement Across Remote APIs. CoRR (2018)
Samuel Yeom, Anupam Datta, Matt Fredrikson
Hunting for Discriminatory Proxies in Linear Regression Models. NeurIPS (2018)
Klas Leino, Linyi Li, Shayak Sen, Anupam Datta, Matt Fredrikson
Influence-Directed Explanations for Deep Convolutional Networks. CoRR (2018)
Samuel Yeom, Matt Fredrikson, Somesh Jha
The Unintended Consequences of Overfitting: Training Data Inference Attacks. CoRR (2017)
Gaurav Srivastava, Saksham Chitkara, Kevin Ku, Swarup Kumar Sahoo, Matt Fredrikson, Jason I. Hong, Yuvraj Agarwal
PrivacyProxy: Leveraging Crowdsourcing and In Situ Traffic Analysis to Detect and Mitigate Information Leakage. CoRR (2017)
Anupam Datta, Matt Fredrikson, Gihyuk Ko, Piotr Mardziel, Shayak Sen
Proxy Non-Discrimination in Data-Driven Systems. CoRR (2017)
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)
Nicolas Papernot, Patrick D. McDaniel, Somesh Jha, Matt Fredrikson, Z. Berkay Celik, Ananthram Swami
The Limitations of Deep Learning in Adversarial Settings. CoRR (2015)
Matt Fredrikson, Somesh Jha, Thomas Ristenpart
Model Inversion Attacks that Exploit Confidence Information and Basic Countermeasures. CCS (2015)
Drew Davidson, Matt Fredrikson, Benjamin Livshits
MoRePriv: mobile OS support for application personalization and privacy. ACSAC (2014)
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)
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)
Chen Chen, Cindy Xide Lin, Matt Fredrikson, Mihai Christodorescu, Xifeng Yan, Jiawei Han
Mining Graph Patterns Efficiently via Randomized Summaries. Proc. VLDB Endow. 2 (1) (2009)
Lorenzo Martignoni, Elizabeth Stinson, Matt Fredrikson, Somesh Jha, John C. Mitchell
A Layered Architecture for Detecting Malicious Behaviors. RAID (2008)