activity
20172020
most citedChameleon: A Hybrid Secure Computation Framework for Machine Learning Applications

51 citations · 67 across the 3 of their papers we have counts for

collaborators

7 papers

eess.IV202014 cited

SynFi: Automatic Synthetic Fingerprint Generation

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. The performance…

cs.CR2019

HEAX: An Architecture for Computing on Encrypted Data

M. Sadegh Riazi, Kim Laine, Blake Pelton +1

With the rapid increase in cloud computing, concerns surrounding data privacy, security, and confidentiality also have been increased significantly. Not only cloud providers are su…

cs.DS2019

SANNS: Scaling Up Secure Approximate k-Nearest Neighbors Search

Hao Chen, Ilaria Chillotti, Yihe Dong +3

The -Nearest Neighbor Search (-NNS) is the backbone of several cloud-based services such as recommender systems, face recognition, and database search on text and images. In…

cs.CR2019

XONN: XNOR-based Oblivious Deep Neural Network Inference

M. Sadegh Riazi, Mohammad Samragh, Hao Chen +3

Advancements in deep learning enable cloud servers to provide inference-as-a-service for clients. In this scenario, clients send their raw data to the server to run the deep learni…

cs.CR2019

ARM2GC: Succinct Garbled Processor for Secure Computation

Ebrahim M. Songhori, M. Sadegh Riazi, Siam U. Hussain +2

We present ARM2GC, a novel secure computation framework based on Yao's Garbled Circuit (GC) protocol and the ARM processor. It allows users to develop privacy-preserving applicatio…

cs.CR201851 cited

Chameleon: A Hybrid Secure Computation Framework for Machine Learning Applications

M. Sadegh Riazi, Christian Weinert, Oleksandr Tkachenko +3

We present Chameleon, a novel hybrid (mixed-protocol) framework for secure function evaluation (SFE) which enables two parties to jointly compute a function without disclosing thei…