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

Security, privacy, & cryptography

Developing technologies that protect data, preserve privacy, and build trustworthy computing systems.

Diagram showing the process of verifying cryptographic code. An algorithm from a standard is converted into a formal specification, while Rust code is converted into a code model. The specification and code model are then compared through proof and verification steps.

Verifying Rust cryptography in SymCrypt, from standards to code

Three white line-style icons centered on a textured blue-to-green gradient background: a shield, a checkmark inside a circle, and an ID card with a user silhouette—representing security, verification, and digital identity.

Vega: Zero-knowledge proofs for digital identity in the age of AI

Project Ire | | three white line icons on an abstract purple background | greater than / less than icon, search icon, shield icon

Ire identifies another LOTUSLITE specimen

Social Reasoning Bench | four icons on a blue to green gradient | person icon, chat bubble icon, chart icon, checklist icon

SocialReasoning-Bench: Measuring whether AI agents act in users’ best interests

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Collaborative Machine Learning Markets

Olga Ohrimenko, Shruti Tople , Sebastian Tschiatschek

Smooth Games Optimization (NeurIPS Workshop) | December 2019

公開日

Dual Isogenies and Their Application to Public-key Compression for Isogeny-based Cryptography

Michael Naehrig, Joost Renes

Advances in Cryptology – ASIACRYPT 2019 | December 2019

プロジェクト

公開日

Neural Malware Control with Deep Reinforcement Learning

Yu Wang, Jack W. Stokes, Mady Marinescu

IEEE Military Communications Conference (MILCOM) | November 2019

プロジェクト

公開日

ScriptNet: Neural Static Analysis for Malicious JavaScript Detection

Jack W. Stokes, Rakshit Agrawal, Geoff McDonald, Matthew Hausknecht

IEEE Military Communications Conference (MILCOM) | November 2019

プロジェクト

公開日

Efficient Multi-Key Homomorphic Encryption with Packed Ciphertexts with Application to Oblivious Neural Network Inference

Hao Chen, Wei Dai, Miran Kim, Yongsoo Song

2019 ACM SIGSAC Conference on Computer and Communications Security | November 2019

動画

In Data we Trust? – or do we? | SIBC 2019 | Santander Bank

November 5, 2019 | E. Glen Weyl

XII Santander International Banking Conference 2019 ‘Banking on trust’. 5th November 2019 In Data we Trust? – or do we? E. Glen Weyl, Founder of the RadicalxChange Foundation and Microsoft’s Office of the Chief Technology…

12:33

公開日

SEEMless: Secure End-to-End Encrypted Messaging with less Trust

Melissa Chase, Apoorvaa Deshpande, Esha Ghosh, Harjasleen Malvai

Computer and Communications Security | November 2019

Github

公開日

Locally Private Gaussian Estimation

Matthew Joseph, Janardhan (Jana) Kulkarni, Jieming Mao, Zhiwei Steven Wu

November 2019

Nuerips 2019 | November 2019

プロジェクト

公開日

RESTler: Stateful REST API Fuzzing

Vaggelis Atlidakis, Patrice Godefroid, Marina Polishchuk

ICSE 2019 | November 2019

動画 Github

公開日

Intelligent REST API Data Fuzzing

Patrice Godefroid, Bo-Yuan Huang, Marina Polishchuk

MSR-TR-2019-37 | November 2019

Microsoft による投稿

Revised version published in ESEC/FSE'2020, November 2020.

Github

Security, privacy, & cryptography

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