publications

Selected publications, patents, and reports in reverse-chronological order — also on Google Scholar. Names containing Wagh are highlighted.

2025

  1. Private Map–Secure Reduce: Infrastructure for Efficient AI Data Markets
    Sameer Wagh, Kenneth Stibler, Shubham Gupta, Lacey Strahm, Irina Bejan, Jiahao Chen, Dave Buckley, Ruchi Bhatia, Jack Bandy, Aayush Agarwal, Andrew Trask
    Technical report
    [PDF] [arXiv]
  2. Secure Enclaves for AI Evaluation
    Anthropic, UK AI Safety Institute, OpenMined
    OpenMined Blog (2025)
    [Blog]
  3. Wave Hello to Privacy: Efficient Mixed-Mode MPC using Wavelet Transforms
    José Reis, Mehmet Ugurbil, Sameer Wagh, Ryan Henry, Miguel de Vega
    Privacy Enhancing Technologies Symposium (PETS) 2025
    [PDF] [Code]

2024

  1. A General Framework of Homomorphic Encryption for Multiple Parties with Non-Interactive Key-Aggregation
    Hyesun Kwak*, Dongwon Lee*, Yongsoo Song*, Sameer Wagh*
    Applied Cryptography and Network Security (ACNS) 2024
    [PDF]

2023

  1. ELSA: Secure Aggregation for Federated Learning with Malicious Actors
    Mayank Rathee, Conghao Shen, Sameer Wagh, Raluca Ada Popa
    IEEE Symposium on Security and Privacy (S&P) 2023
    [PDF]
  2. Code Analysis for Sensitive Data using LLMs
    Sameer Wagh, Kartik Chopra, Sid Roy
    U.S. Patent Application Serial No. 18/484,058 (2023)
  3. Federated Learning Platform and Methods for using same
    Sameer Wagh, Kartik Chopra, Sid Roy
    U.S. Patent Application Serial No. 18/447,874 (2023)

2022

  1. Piranha: A GPU Platform for Secure Computation
    Jean-Luc Watson, Sameer Wagh, Raluca Ada Popa
    USENIX Security Symposium 2022
    [PDF] [Code]
  2. Pika: Secure Computation using Function Secret Sharing over Rings
    Sameer Wagh
    Privacy Enhancing Technologies Symposium (PETS) 2022
    [PDF]
  3. BarnOwl: Secure Comparisons using Silent Pseudorandom Correlation Generators
    Sameer Wagh
    Technical Report (2022)
    [PDF]
  4. Towards Probabilistic Verification of Machine Unlearning
    David Marco Sommer, Liwei Song, Sameer Wagh, Prateek Mittal
    Privacy Enhancing Technologies Symposium (PETS) 2022
    [PDF] [Code]

2021

  1. Rabbit: Efficient Comparison for Secure Multi-Party Computation
    Eleftheria Makri*, Dragoș Rotaru*, Frederik Vercauteren*, Sameer Wagh*
    Financial Cryptography and Data Security (FC) 2021
    [PDF] [Code]
  2. FALCON: Honest-Majority Maliciously Secure Framework for Private Deep Learning
    Sameer Wagh, Shruti Tople, Fabrice Benhamouda, Eyal Kushilevitz, Prateek Mittal, Tal Rabin
    Privacy Enhancing Technologies Symposium (PETS) 2021
    [PDF] [Code] [📰 News][📰 News] [🏆 Award][🏆 Award] [💥 Impact][💥 Impact]
  3. DP-Cryptography: Marrying Differential Privacy and Cryptography in Emerging Applications
    Sameer Wagh, Xi He, Ashwin Machanavajjhala, Prateek Mittal
    Communications of the ACM (CACM) 2021
    [PDF]
  4. Protecting Privacy through Homomorphic Encryption
    Sameer Wagh
    Book chapter, Springer (eds. Kristin Lauter, Wei Dai, Kim Laine) 2021
    [Link]

2020

  1. New Directions in Efficient Privacy-Preserving Machine Learning
    Sameer Wagh
    Ph.D. Thesis, Princeton University, 2020
    [PDF]
  2. Maliciously Secure Matrix Multiplication with Applications to Private Deep Learning
    Hao Chen*, Miran Kim*, Ilya Razenshteyn*, Dragoș Rotaru*, Yongsoo Song*, Sameer Wagh*
    Theory and Application of Cryptology (AsiaCrypt) 2020
    [PDF] [Code]

2019

  1. Guard Placement Attacks on Path Selection Algorithms for Tor
    Gerry Wan, Aaron Johnson, Ryan Wails, Sameer Wagh, Prateek Mittal
    Privacy Enhancing Technologies Symposium (PETS) 2019
    [PDF] [Code]
  2. SecureNN: 3-Party Secure Computation for Neural Network Training
    Sameer Wagh, Divya Gupta, Nishanth Chandran
    Privacy Enhancing Technologies Symposium (PETS) 2019
    [PDF] [Code] [💥 Impact][💥 Impact]
  3. DPSelect: A Differential Privacy Based Guard Relay Selection Algorithm for Tor
    Hans Hanley, Yixin Sun, Sameer Wagh, Prateek Mittal
    Privacy Enhancing Technologies Symposium (PETS) 2019
    [PDF]
  4. Private Deep Neural Network Training
    Sameer Wagh, Divya Gupta, Nishanth Chandran
    U.S. Patent 10,460,234 (2019)
    [Link]

2018

  1. Differentially Private Oblivious RAM
    Sameer Wagh, Paul Cuff, Prateek Mittal
    Privacy Enhancing Technologies Symposium (PETS) 2018
    [PDF] [Code] [📰 News]

2017

  1. The Pyramid Scheme: Oblivious RAM for Trusted Processors
    Olya Ohrimenko, Lawrence Esswood, Sameer Wagh, Felix Schuster, Manuel Costa
    Technical Report (2017)
    [PDF]
  2. Camouflage: Memory Traffic Shaping to Mitigate Timing Attacks
    Yanqi Zhou, Sameer Wagh, Prateek Mittal, David Wentzlaff
    High Performance Computer Architecture (HPCA) 2017
    [PDF]
  3. Tunable Oblivious RAM
    Sameer Wagh, Paul Cuff, Prateek Mittal
    U.S. Patent US20170185534 (2017)
    [Link]

Also on DBLP. * denotes alphabetical author order.