illustration of lock, four asterisks and a shield with a fingerprint on it on a green gradient background

Security, privacy, and cryptography

Leveraging Large Language Models for Automated Proof Synthesis in Rust

photos of PhD students Anunay Kulshrestha and Karan Newatia with a photo of Senior Cryptographer Josh Benaloh in the middle with a microphone icon on a blue and purple gradient background

Intern Insights: Dr. Josh Benaloh with Anunay Kulshrestha and Karan Newatia

Bayes Security (β*, higher better) of DP-SGD against membership and attribute inference on the Adult and Purchase datasets as a function of the number of training steps. The green dashed line shows the corresponding DP budget (ε). Membership and attribute inference curves decrease monotonically as the model is trained for longer and the accuracy and DP budget grow.

Closed-Form Bounds for DP-SGD against Record-level Inference

ProvCam: A Camera Module with Self-Contained TCB for Producing Verifiable Videos

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Published Date

Video

Faculty Summit 2016: Hot Topics

February 26, 2020 | Lucy Vanderwende, Ran Gilad-Bachrach, Bryan Parno and Nikhil Swamy, Neil Dalchau

Generating Natural Questions About an Image CryptoNets: Machine Learning Inference on Encrypted Data Everest: Deploying Verified-Secure Implementations in the HTTPS Ecosystem Molecular Programming

0:42:39

Project

Project Laplace

The broad goal of Project Laplace is to enable privacy-preserving data analysis and machine learning using differential privacy.

Video

AI Security Engineering—Modeling/Detecting/Mitigating New Vulnerabilities

February 26, 2020 | Andrew Marshall, Jugal Parikh, Raul Rojas

AI and machine learning present a litany of unmitigated security threats. Research is pivoting from contrived vulns to weaponized exploitation. As a security engineer, how do I protect and defend my services against these threats?…

53:44

Podcast

Democratizing data, thinking backwards and setting North Star goals with Dr. Donald Kossmann

February 19, 2020

Dr. Donald Kossmann is a Distinguished Scientist who thinks big, and as the Director of Microsoft Research’s flagship lab in Redmond, it’s his job to inspire others to think big, too. But don’t be fooled.…

image of Donald Kossmann for the Microsoft Research Podcast

Publication

A Case for Humans-in-the-Loop: Decisions in the Presence of Erroneous Algorithmic Scores

Maria De-Arteaga, Riccardo Fogliato, Alex Chouldechova

2020 Human Factors in Computing Systems | February 2020

Tool

ElectionGuard

ElectionGuard is an open source software development kit (SDK) that makes voting more secure, transparent and accessible. Announced on at the Build developer conference (opens in new tab), ElectionGuard enables end-to-end verification of elections as well as support…

GitHub

Publication

Actor Critic Deep Reinforcement Learning for Neural Malware Control

Yu Wang, Jack W. Stokes, Mady Marinescu

Proceedings of the AAAI Conference on Artificial Intelligence | February 2020

Event

Homomorphic Encryption Workshop 2020

February 6, 2020 – February 7, 2020 | Redmond, Washington, USA

This meeting will be an opportunity for us to reflect on the progress we’ve made and to chart a path forward together as a community. We will take this opportunity together to articulate the community…

Homomorphic Encryption Standardization Workshop

Publication

Witness Indistinguishability For Any Single-Round Argument With Applications To Access Control

Zvika Brakerski, Yael Tauman Kalai

IACR International Conference on Public-Key Cryptography | February 2020

Publication

Privacy-Aware Personalized Entity Representations for Improved User Understanding

Levi Melnick, Hussein Elmessilhy, Vassilis Polychronopoulos, Gilsinia Lopez, Yuancheng Tu, Omar Zia Khan, Ye-Yi Wang, Chris Quirk

PrivateNLP @ WSDM | February 2020

Security, privacy, and cryptography

Highlights