Search Results for author:
Found 6 papers, 1 papers with code
SynFi: Automatic Synthetic Fingerprint Generation
Authentication and identification methods based on human fingerprints are ubiquitous in several systems ranging from government organizations to consumer products.
HEAX: An Architecture for Computing on Encrypted Data
Building on top of NTT engine, we design a novel architecture for computation on homomorphically encrypted data.
SANNS: Scaling Up Secure Approximate k-Nearest Neighbors Search
In this paper, we introduce SANNS, a system for secure $k$-NNS that keeps client's query and the search result confidential.
Chameleon: A Hybrid Secure Computation Framework for Machine Learning Applications
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.
DeepSecure: Scalable Provably-Secure Deep Learning
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
Sub-Linear Privacy-Preserving Near-Neighbor Search
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.
