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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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Publication

Distinguishing Attacks from Legitimate Traffic at an Authentication Server

MSR-TR-2018-19 | June 2018

Publication

Robust Neural Malware Detection Models for Emulation Sequence Learning

Rakshit Agrawal, Jack W. Stokes, Mady Marinescu, Karthik Selvaraj

2018 Military Communications Conference | June 2018

Video

City Data Exchange and Edge Analytics: A case for an Open Stack

June 19, 2018 | Bharadwaj Amrutur

The Indian government is attempting an ambitious aspirational move to “smarten” India’s cities. We do a deep dive analysis of a recent RFP for the same, which has been put out by the city of…

CityDataExchangeandEdgeAnalytics STILL

Video

Machine Learning with Limited Signals at Mote-Scale

June 14, 2018 | Anish Arora

This talk describes the growing role of machine learning in battery-powered wireless sensor networks being deployed in rural and urban areas for environmental and wildlife projection. Specifically, we will discuss radar-based HornNet, deployed in a…

machine learning with limited sign STILL

Publication

Generic Round-Function-Recovery Attacks for Feistel Networks over Small Domains

Betül Durak, Serge Vaudenay

ACNS | June 2018

Publication

SandTrap: Tracking Information Flows On Demand with Parallel Permissions

Ali Razeen, Alvin R. Lebeck, David H. Liu, Alexander Meijer, Valentin Pistol, Landon Cox

MobiSys | June 2018

Publication

Proceedings of the 2nd {ACM} Workshop on Blockchains, Cryptocurrencies, and Contracts, BCC@AsiaCCS 2018, Incheon, Republic of Korea, June 4, 2018

Satya Lokam, Sushmita Ruj, Kouichi Sakurai

Published by ACM SIGSAC | June 2018, Vol 1 | 1 edition

Editor(s): Satya V. Lokam and Sushmita Ruj and Kouichi Sakurai

ISBN: 978-1-4503-5758-6

Publication

DeepSecure: Scalable Provably-Secure Deep Learning

Bita Darvish Rouhani, Sadegh Riazi, Farinaz Koushanfar

Design Automation Conference (DAC) | June 2018

Publication

MAXelerator: FPGA Accelerator for Privacy Preserving Multiply-Accumulate (MAC) on Cloud Servers

Siam U. Hussain, Bita Rouhani, Mohammad Ghasemzadeh, Farinaz Koushanfar

Design Automation Conference (DAC) | June 2018

Publication

Detecting Malicious PowerShell Commands using Deep Neural Networks

Danny Hendler, Shay Kels, Amir Rubin

Computer and Communications Security | May 2018

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