1 code implementation • 16 Feb 2020 • M. Sadegh Riazi, Seyed M. Chavoshian, Farinaz Koushanfar
Authentication and identification methods based on human fingerprints are ubiquitous in several systems ranging from government organizations to consumer products.
no code implementations • 20 Sep 2019 • M. Sadegh Riazi, Kim Laine, Blake Pelton, Wei Dai
Building on top of NTT engine, we design a novel architecture for computation on homomorphically encrypted data.
no code implementations • 3 Apr 2019 • Hao Chen, Ilaria Chillotti, Yihe Dong, Oxana Poburinnaya, Ilya Razenshteyn, M. Sadegh Riazi
In this paper, we introduce SANNS, a system for secure $k$-NNS that keeps client's query and the search result confidential.
no code implementations • 10 Jan 2018 • M. Sadegh Riazi, Christian Weinert, Oleksandr Tkachenko, Ebrahim. M. Songhori, Thomas Schneider, Farinaz Koushanfar
Chameleon departs from the common assumption of additive or linear secret sharing models where three or more parties need to communicate in the online phase: the framework allows two parties with private inputs to communicate in the online phase under the assumption of a third node generating correlated randomness in an offline phase.
no code implementations • 24 May 2017 • Bita Darvish Rouhani, M. Sadegh Riazi, Farinaz Koushanfar
This paper proposes DeepSecure, a novel framework that enables scalable execution of the state-of-the-art Deep Learning (DL) models in a privacy-preserving setting.
Cryptography and Security
no code implementations • 6 Dec 2016 • M. Sadegh Riazi, Beidi Chen, Anshumali Shrivastava, Dan Wallach, Farinaz Koushanfar
In Near-Neighbor Search (NNS), a new client queries a database (held by a server) for the most similar data (near-neighbors) given a certain similarity metric.