Matt Fredrikson

According to our database1, Matt Fredrikson authored at least 81 papers between 2008 and 2023.

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Bibliography

2023
Transfer Attacks and Defenses for Large Language Models on Coding Tasks.
CoRR, 2023

Is Certifying 𝓁<sub>p</sub> Robustness Still Worthwhile?
CoRR, 2023

A Recipe for Improved Certifiable Robustness: Capacity and Data.
CoRR, 2023

Representation Engineering: A Top-Down Approach to AI Transparency.
CoRR, 2023

Universal and Transferable Adversarial Attacks on Aligned Language Models.
CoRR, 2023

Scaling in Depth: Unlocking Robustness Certification on ImageNet.
CoRR, 2023

Learning Modulo Theories.
CoRR, 2023

Grounding Neural Inference with Satisfiability Modulo Theories.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Unlocking Deterministic Robustness Certification on ImageNet.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

On the Perils of Cascading Robust Classifiers.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
Degradation Attacks on Certifiably Robust Neural Networks.
Trans. Mach. Learn. Res., 2022

Black-Box Audits for Group Distribution Shifts.
CoRR, 2022

Faithful Explanations for Deep Graph Models.
CoRR, 2022

Enhancing the insertion of NOP instructions to obfuscate malware via deep reinforcement learning.
Comput. Secur., 2022

Privacy-Preserving Case-Based Explanations: Enabling Visual Interpretability by Protecting Privacy.
IEEE Access, 2022

Protecting user data through ephemeral ownership of IoT devices.
Proceedings of the MobiSys '22: The 20th Annual International Conference on Mobile Systems, Applications and Services, Portland, Oregon, 27 June 2022, 2022

TEO: ephemeral ownership for IoT devices to provide granular data control.
Proceedings of the MobiSys '22: The 20th Annual International Conference on Mobile Systems, Applications and Services, Portland, Oregon, 27 June 2022, 2022

Robust Models Are More Interpretable Because Attributions Look Normal.
Proceedings of the International Conference on Machine Learning, 2022

Consistent Counterfactuals for Deep Models.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Selective Ensembles for Consistent Predictions.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Self-correcting Neural Networks for Safe Classification.
Proceedings of the Software Verification and Formal Methods for ML-Enabled Autonomous Systems, 2022

2021
Consistent Counterfactuals for Deep Models.
CoRR, 2021

Self-Repairing Neural Networks: Provable Safety for Deep Networks via Dynamic Repair.
CoRR, 2021

The Design of the User Interfaces for Privacy Enhancements for Android.
CoRR, 2021

Boundary Attributions Provide Normal (Vector) Explanations.
CoRR, 2021

Netter: Probabilistic, Stateful Network Models.
Proceedings of the Verification, Model Checking, and Abstract Interpretation, 2021

Capture: Centralized Library Management for Heterogeneous IoT Devices.
Proceedings of the 30th USENIX Security Symposium, 2021

Relaxing Local Robustness.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Exploring Conceptual Soundness with TruLens.
Proceedings of the NeurIPS 2021 Competitions and Demonstrations Track, 2021

Machine Learning Explainability and Robustness: Connected at the Hip.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Globally-Robust Neural Networks.
Proceedings of the 38th International Conference on Machine Learning, 2021

Fast Geometric Projections for Local Robustness Certification.
Proceedings of the 9th International Conference on Learning Representations, 2021

Leave-one-out Unfairness.
Proceedings of the FAccT '21: 2021 ACM Conference on Fairness, 2021

Automating Audit with Policy Inference.
Proceedings of the 34th IEEE Computer Security Foundations Symposium, 2021

2020
Overfitting, robustness, and malicious algorithms: A study of potential causes of privacy risk in machine learning.
J. Comput. Secur., 2020

Stolen Memories: Leveraging Model Memorization for Calibrated White-Box Membership Inference.
Proceedings of the 29th USENIX Security Symposium, 2020

Smoothed Geometry for Robust Attribution.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Reconciling noninterference and gradual typing.
Proceedings of the LICS '20: 35th Annual ACM/IEEE Symposium on Logic in Computer Science, 2020

Individual Fairness Revisited: Transferring Techniques from Adversarial Robustness.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

FlipTest: fairness testing via optimal transport.
Proceedings of the FAT* '20: Conference on Fairness, 2020

Interpreting Interpretations: Organizing Attribution Methods by Criteria.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

Contextual and Granular Policy Enforcement in Database-backed Applications.
Proceedings of the ASIA CCS '20: The 15th ACM Asia Conference on Computer and Communications Security, 2020

Learning Fair Representations for Kernel Models.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Influence Paths for Characterizing Subject-Verb Number Agreement in LSTM Language Models.
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2019
FlipTest: Fairness Auditing via Optimal Transport.
CoRR, 2019

Feature-Wise Bias Amplification.
Proceedings of the 7th International Conference on Learning Representations, 2019

2018
Why Are They Collecting My Data?: Inferring the Purposes of Network Traffic in Mobile Apps.
Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2018

ESTRELA: Automated Policy Enforcement Across Remote APIs.
CoRR, 2018

Supervising Feature Influence.
CoRR, 2018

Hunting for Discriminatory Proxies in Linear Regression Models.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Influence-Directed Explanations for Deep Convolutional Networks.
Proceedings of the IEEE International Test Conference, 2018

Quantitative underpinnings of secure, graceful degradation: poster.
Proceedings of the 5th Annual Symposium and Bootcamp on Hot Topics in the Science of Security, 2018

Privacy Risk in Machine Learning: Analyzing the Connection to Overfitting.
Proceedings of the 31st IEEE Computer Security Foundations Symposium, 2018

2017
PrivacyStreams: Enabling Transparency in Personal Data Processing for Mobile Apps.
Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2017

The Unintended Consequences of Overfitting: Training Data Inference Attacks.
CoRR, 2017

PrivacyProxy: Leveraging Crowdsourcing and In Situ Traffic Analysis to Detect and Mitigate Information Leakage.
CoRR, 2017

Proxy Non-Discrimination in Data-Driven Systems.
CoRR, 2017

Verifying and Synthesizing Constant-Resource Implementations with Types.
Proceedings of the 2017 IEEE Symposium on Security and Privacy, 2017

Use Privacy in Data-Driven Systems: Theory and Experiments with Machine Learnt Programs.
Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security, 2017

2016
The Limitations of Deep Learning in Adversarial Settings.
Proceedings of the IEEE European Symposium on Security and Privacy, 2016

A Methodology for Formalizing Model-Inversion Attacks.
Proceedings of the IEEE 29th Computer Security Foundations Symposium, 2016

2015
Surreptitiously Weakening Cryptographic Systems.
IACR Cryptol. ePrint Arch., 2015

Revisiting Differentially Private Regression: Lessons From Learning Theory and their Consequences.
CoRR, 2015

Model Inversion Attacks that Exploit Confidence Information and Basic Countermeasures.
Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security, 2015

2014
Privacy in Pharmacogenetics: An End-to-End Case Study of Personalized Warfarin Dosing.
Proceedings of the 23rd USENIX Security Symposium, San Diego, CA, USA, August 20-22, 2014., 2014

ZØ: An Optimizing Distributing Zero-Knowledge Compiler.
Proceedings of the 23rd USENIX Security Symposium, San Diego, CA, USA, August 20-22, 2014., 2014

On the Practical Exploitability of Dual EC in TLS Implementations.
Proceedings of the 23rd USENIX Security Symposium, San Diego, CA, USA, August 20-22, 2014., 2014

Satisfiability modulo counting: a new approach for analyzing privacy properties.
Proceedings of the Joint Meeting of the Twenty-Third EACSL Annual Conference on Computer Science Logic (CSL) and the Twenty-Ninth Annual ACM/IEEE Symposium on Logic in Computer Science (LICS), 2014

MoRePriv: mobile OS support for application personalization and privacy.
Proceedings of the 30th Annual Computer Security Applications Conference, 2014

2012
Efficient Runtime Policy Enforcement Using Counterexample-Guided Abstraction Refinement.
Proceedings of the Computer Aided Verification - 24th International Conference, 2012

2011
End-to-End Software Diversification of Internet Services.
Proceedings of the Moving Target Defense, 2011

Verified Security for Browser Extensions.
Proceedings of the 32nd IEEE Symposium on Security and Privacy, 2011

RePriv: Re-imagining Content Personalization and In-browser Privacy.
Proceedings of the 32nd IEEE Symposium on Security and Privacy, 2011

Dynamic Behavior Matching: A Complexity Analysis and New Approximation Algorithms.
Proceedings of the Automated Deduction - CADE-23 - 23rd International Conference on Automated Deduction, Wroclaw, Poland, July 31, 2011

2010
A Declarative Framework for Intrusion Analysis.
Proceedings of the Cyber Situational Awareness - Issues and Research, 2010

Cyber SA: Situational Awareness for Cyber Defense.
Proceedings of the Cyber Situational Awareness - Issues and Research, 2010

Automatic Generation of Remediation Procedures for Malware Infections.
Proceedings of the 19th USENIX Security Symposium, 2010

Synthesizing Near-Optimal Malware Specifications from Suspicious Behaviors.
Proceedings of the 31st IEEE Symposium on Security and Privacy, 2010

Mining Large Information Networks by Graph Summarization.
Proceedings of the Link Mining: Models, Algorithms, and Applications, 2010

2009
Mining Graph Patterns Efficiently via Randomized Summaries.
Proc. VLDB Endow., 2009

2008
A Layered Architecture for Detecting Malicious Behaviors.
Proceedings of the Recent Advances in Intrusion Detection, 11th International Symposium, 2008


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