alpha-leanTAP: A Declarative Theorem Prover for First-Order Classical Logic. - Joseph P. Near; William E. Byrd; Daniel P. Friedman (ICLP, 2008)

Equality and hashing for (almost) free: Generating implementations from abstraction functions. - Derek Rayside; Zev Benjamin; Rishabh Singh; Joseph P. Near; Aleksandar Milicevic; Daniel Jackson 001 (ICSE, 2009)

An Imperative Extension to Alloy. - Joseph P. Near; Daniel Jackson 001 (ASM, 2010)

From Relational Specifications to Logic Programs. - Joseph P. Near (ICLP (Technical Communications), 2010)

A lightweight code analysis and its role in evaluation of a dependability case. - Joseph P. Near; Aleksandar Milicevic; Eunsuk Kang; Daniel Jackson 001 (ICSE, 2011)

Rubicon: bounded verification of web applications. - Joseph P. Near; Daniel Jackson 001 (SIGSOFT FSE, 2012)

Applications and extensions of Alloy: past, present and future. - Emina Torlak; Mana Taghdiri; Greg Dennis; Joseph P. Near (Math. Struct. Comput. Sci., 2013)

Derailer: interactive security analysis for web applications. - Joseph P. Near; Daniel Jackson 001 (ASE, 2014)

Finding security bugs in web applications using domain-specific static analysis. - Joseph P. Near (2015)

Finding security bugs in web applications using a catalog of access control patterns. - Joseph P. Near; Daniel Jackson 001 (ICSE, 2016)

Practical Differential Privacy for SQL Queries Using Elastic Sensitivity. - Noah M. Johnson; Joseph P. Near; Dawn Xiaodong Song (CoRR, 2017)

Chorus: Differential Privacy via Query Rewriting. - Noah M. Johnson; Joseph P. Near; Joseph M. Hellerstein; Dawn Song (CoRR, 2018)

Towards Practical Differential Privacy for SQL Queries. - Noah M. Johnson; Joseph P. Near; Dawn Song (Proc. VLDB Endow., 2018)

Towards Practical Differentially Private Convex Optimization. - Roger Iyengar; Joseph P. Near; Dawn Song; Om Thakkar 001; Abhradeep Thakurta; Lun Wang 001 (IEEE Symposium on Security and Privacy, 2019)

Data Capsule: A New Paradigm for Automatic Compliance with Data Privacy Regulations. - Lun Wang 001; Joseph P. Near; Neel Somani; Peng Gao 008; Andrew Low; David Dao; Dawn Song (Poly/DMAH@VLDB, 2019)

Alloy*: a general-purpose higher-order relational constraint solver. - Aleksandar Milicevic; Joseph P. Near; Eunsuk Kang; Daniel Jackson 001 (Formal Methods Syst. Des., 2019)

Duet: an expressive higher-order language and linear type system for statically enforcing differential privacy. - Joseph P. Near; David Darais; Chike Abuah; Tim Stevens; Pranav Gaddamadugu; Lun Wang 001; Neel Somani; Mu Zhang 001; Nikhil Sharma; Alex Shan; Dawn Song (Proc. ACM Program. Lang., 2019)

Chorus: a Programming Framework for Building Scalable Differential Privacy Mechanisms. - Noah M. Johnson; Joseph P. Near; Joseph M. Hellerstein; Dawn Song (EuroS&P, 2020)

Towards a Measure of Individual Fairness for Deep Learning. - Krystal Maughan; Joseph P. Near (CoRR, 2020)

DuetSGX: Differential Privacy with Secure Hardware. - Phillip Nguyen; Alex Silence; David Darais; Joseph P. Near (CoRR, 2020)

Contextual Linear Types for Differential Privacy. - Matías Toro; David Darais; Chike Abuah; Joe Near; Federico Olmedo; Éric Tanter (CoRR, 2020)

Towards Auditability for Fairness in Deep Learning. - Ivoline C. Ngong; Krystal Maughan; Joseph P. Near (CoRR, 2020)

PrivFramework: A System for Configurable and Automated Privacy Policy Compliance. - Usmann Khan; Lun Wang 001; Jithendaraa Subramanian; Joseph P. Near; Dawn Song (CoRR, 2020)

Zero Knowledge Static Program Analysis. - Zhiyong Fang; David Darais; Joseph P. Near; Yupeng Zhang 001 (CCS, 2021)

DDUO: General-Purpose Dynamic Analysis for Differential Privacy. - Chike Abuah; Alex Silence; David Darais; Joseph P. Near (CSF, 2021)

Solo: Enforcing Differential Privacy Without Fancy Types. - Chike Abuah; David Darais; Joseph P. Near (CoRR, 2021)

Do I Get the Privacy I Need? Benchmarking Utility in Differential Privacy Libraries. - Gonzalo Munilla Garrido; Joseph P. Near; Muhammad Aitsam; Warren He; Roman Matzutt; Florian Matthes (CoRR, 2021)

Methods for Host-based Intrusion Detection with Deep Learning. - John H. Ring; Colin Michael Van Oort; Samson Durst; Vanessa White; Joseph P. Near; Christian Skalka (DTRAP, 2021)

Differential Privacy for Databases. - Joseph P. Near; Xi He 001 (Found. Trends Databases, 2021)

Efficient Differentially Private Secure Aggregation for Federated Learning via Hardness of Learning with Errors. - Timothy Stevens; Christian Skalka; Christelle Vincent; John H. Ring; Samuel Clark; Joseph P. Near (USENIX Security Symposium, 2022)

PrivGuard: Privacy Regulation Compliance Made Easier. - Lun Wang 001; Usmann Khan; Joseph P. Near; Qi Pang; Jithendaraa Subramanian; Neel Somani; Peng Gao 008; Andrew Low; Dawn Song (USENIX Security Symposium, 2022)

Secret Sharing Sharing For Highly Scalable Secure Aggregation. - Timothy Stevens; Joseph P. Near; Christian Skalka (CoRR, 2022)

Prediction Sensitivity: Continual Audit of Counterfactual Fairness in Deployed Classifiers. - Krystal Maughan; Ivoline C. Ngong; Joseph P. Near (CoRR, 2022)

Improving Utility for Privacy-Preserving Analysis of Correlated Columns using Pufferfish Privacy. - Krystal Maughan; Joseph P. Near (CoRR, 2022)

Solo: a lightweight static analysis for differential privacy. - Chike Abuah; David Darais; Joseph P. Near (Proc. ACM Program. Lang., 2022)

Contextual Linear Types for Differential Privacy. - Matías Toro; David Darais; Chike Abuah; Joseph P. Near; Damián Árquez; Federico Olmedo; Éric Tanter (ACM Trans. Program. Lang. Syst., 2023)

Language-Based Security for Low-Level MPC. - Christian Skalka; Joseph P. Near (PPDP, 2024)

Olympia: A Simulation Framework for Evaluating the Concrete Scalability of Secure Aggregation Protocols. - Ivoline C. Ngong; Nicholas Gibson; Joseph P. Near (SaTML, 2024)

Energy Efficient Data Routing for IoT Networks Using Genetic Algorithm. - Farzana Akhter; Joseph P. Near (SmartNets, 2024)

Evaluating the Usability of Differential Privacy Tools with Data Practitioners. - Ivoline C. Ngong; Brad Stenger; Joseph P. Near; Yuanyuan Feng (SOUPS @ USENIX Security Symposium, 2024)

DT-SIM: Property-Based Testing for MPC Security. - Mako Bates; Joseph P. Near (CoRR, 2024)

We Know I Know You Know; Choreographic Programming With Multicast and Multiply Located Values. - Mako Bates; Joseph P. Near (CoRR, 2024)

MultiChor: Census Polymorphic Choreographic Programming with Multiply Located Values. - Mako Bates; Syed Jafri; Joseph P. Near (CoRR, 2024)

Proceedings of the 2024 miniKanren and Relational Programming Workshop. - Ekaterina Verbitskaia; Joseph P. Near (CoRR, 2024)

SoK: Usability Studies in Differential Privacy. - Onyinye Dibia; Brad Stenger; Steven Baldasty; Mako Bates; Ivoline C. Ngong; Yuanyuan Feng; Joseph P. Near (CoRR, 2024)

Foldable, Recursive Proofs of Isogeny Computation with Reduced Time Complexity. - Krystal Maughan; Joseph P. Near; Christelle Vincent (IACR Cryptol. ePrint Arch., 2024)

SMT-Boosted Security Types for Low-Level MPC. - Christian Skalka; Joseph P. Near (ESOP (2), 2025)

Differentially Private Learning Needs Better Model Initialization and Self-Distillation. - Ivoline C. Ngong; Joseph P. Near; Niloofar Mireshghallah (NAACL (Long Papers), 2025)

Efficient, Portable, Census-Polymorphic Choreographic Programming. - Mako Bates; Shun Kashiwa; Syed Jafri; Gan Shen; Lindsey Kuper; Joseph P. Near (Proc. ACM Program. Lang., 2025)

SoK: Usability Studies in Differential Privacy. - Onyinye Dibia; Prianka Bhattacharjee; Brad Stenger; Steven Baldasty; Mako Bates; Ivoline C. Ngong; Yuanyuan Feng; Joseph P. Near (Proc. Priv. Enhancing Technol., 2025)

Aim High, Stay Private: Differentially Private Synthetic Data Enables Public Release of Behavioral Health Information with High Utility. - Mohsen Ghasemizade; Juniper L. Lovato; Christopher M. Danforth; Peter Sheridan Dodds; Laura SP Bloomfield; Matthew Price; Team LEMURS; Joseph P. Near (CoRR, 2025)

"We Need a Standard": Toward an Expert-Informed Privacy Label for Differential Privacy. - Onyinye Dibia; Mengyi Lu; Prianka Bhattacharjee; Joseph P. Near; Yuanyuan Feng (CoRR, 2025)