| Consistent Counterfactuals for Deep Models | 0 | 0.34 | 2022 |
| Exploring Conceptual Soundness with TruLens. | 0 | 0.34 | 2021 |
| Globally-Robust Neural Networks | 0 | 0.34 | 2021 |
| Netter - Probabilistic, Stateful Network Models. | 0 | 0.34 | 2021 |
| Machine Learning Explainability and Robustness: Connected at the Hip | 0 | 0.34 | 2021 |
| Fast Geometric Projections for Local Robustness Certification | 0 | 0.34 | 2021 |
| Automating Audit with Policy Inference | 0 | 0.34 | 2021 |
| Smoothed Geometry for Robust Attribution | 0 | 0.34 | 2020 |
| Contextual and Granular Policy Enforcement in Database-backed Applications | 0 | 0.34 | 2020 |
| Individual Fairness Revisited: Transferring Techniques from Adversarial Robustness | 0 | 0.34 | 2020 |
| Reconciling noninterference and gradual typing | 0 | 0.34 | 2020 |
| Interpreting Interpretations: Organizing Attribution Methods by Criteria | 0 | 0.34 | 2020 |
| Overfitting, robustness, and malicious algorithms: A study of potential causes of privacy risk in machine learning. | 0 | 0.34 | 2020 |
| Influence Paths for Characterizing Subject-Verb Number Agreement in LSTM Language Models | 0 | 0.34 | 2020 |
| FlipTest: Fairness Auditing via Optimal Transport. | 0 | 0.34 | 2019 |
| Quantitative underpinnings of secure, graceful degradation: poster. | 0 | 0.34 | 2018 |
| Verifying and Synthesizing Constant-Resource Implementations with Types | 4 | 0.40 | 2018 |
| Hunting for Discriminatory Proxies in Linear Regression Models. | 0 | 0.34 | 2018 |
| Why Are They Collecting My Data?: Inferring the Purposes of Network Traffic in Mobile Apps. | 2 | 0.36 | 2018 |
| ESTRELA: Automated Policy Enforcement Across Remote APIs. | 0 | 0.34 | 2018 |
| Supervising Feature Influence. | 0 | 0.34 | 2018 |
| Feature-Wise Bias Amplification. | 0 | 0.34 | 2018 |
| Privacy Risk in Machine Learning: Analyzing the Connection to Overfitting | 23 | 0.70 | 2018 |
| Use Privacy in Data-Driven Systems: Theory and Experiments with Machine Learnt Programs. | 6 | 0.45 | 2017 |
| Proxy Non-Discrimination in Data-Driven Systems. | 4 | 0.47 | 2017 |
| PrivacyStreams: Enabling Transparency in Personal Data Processing for Mobile Apps. | 2 | 0.36 | 2017 |
| The Unintended Consequences of Overfitting: Training Data Inference Attacks. | 1 | 0.35 | 2017 |
| PrivacyProxy: Leveraging Crowdsourcing and In Situ Traffic Analysis to Detect and Mitigate Information Leakage. | 1 | 0.35 | 2017 |
| A Methodology for Formalizing Model-Inversion Attacks | 8 | 0.49 | 2016 |
| Model Inversion Attacks that Exploit Confidence Information and Basic Countermeasures | 156 | 4.80 | 2015 |
| Surreptitiously Weakening Cryptographic Systems. | 0 | 0.34 | 2015 |
| Revisiting Differentially Private Regression: Lessons From Learning Theory and their Consequences. | 0 | 0.34 | 2015 |
| The Limitations of Deep Learning in Adversarial Settings | 391 | 16.69 | 2015 |
| ZØ: an optimizing distributing zero-knowledge compiler | 5 | 0.39 | 2014 |
| Satisfiability modulo counting: a new approach for analyzing privacy properties | 9 | 0.45 | 2014 |
| On the practical exploitability of dual EC in TLS implementations | 5 | 0.82 | 2014 |
| Privacy in pharmacogenetics: an end-to-end case study of personalized warfarin dosing | 72 | 2.10 | 2014 |
| MoRePriv: mobile OS support for application personalization and privacy. | 12 | 0.61 | 2014 |
| Efficient runtime policy enforcement using counterexample-guided abstraction refinement | 6 | 0.53 | 2012 |
| Dynamic behavior matching: a complexity analysis and new approximation algorithms | 6 | 0.45 | 2011 |
| RePriv: Re-imagining Content Personalization and In-browser Privacy | 36 | 1.38 | 2011 |
| Verified Security for Browser Extensions | 47 | 2.55 | 2011 |
| Synthesizing Near-Optimal Malware Specifications from Suspicious Behaviors | 90 | 2.80 | 2010 |
| Automatic generation of remediation procedures for malware infections | 10 | 0.56 | 2010 |
| Mining graph patterns efficiently via randomized summaries | 29 | 1.06 | 2009 |
| A Layered Architecture for Detecting Malicious Behaviors | 47 | 2.01 | 2008 |
