Blind quantum machine learning with quantum bipartite correlator
Distributed quantum computing is a promising computational paradigm for performing
computations that are beyond the reach of individual quantum devices. Privacy in distributed …
computations that are beyond the reach of individual quantum devices. Privacy in distributed …
Privacy-Preserving Data Fusion for Traffic State Estimation: A Vertical Federated Learning Approach
This paper proposes a privacy-preserving data fusion method for traffic state estimation
(TSE). Unlike existing works that assume all data sources to be accessible by a single …
(TSE). Unlike existing works that assume all data sources to be accessible by a single …
Rhombus: Fast Homomorphic Matrix-Vector Multiplication for Secure Two-Party Inference
J He, K Yang, G Tang, Z Huang, L Lin, C Wei… - Cryptology ePrint …, 2024 - eprint.iacr.org
Abstract We present $\textit {Rhombus} $, a new secure matrix-vector multiplication (MVM)
protocol in the semi-honest two-party setting, which is able to be seamlessly integrated into …
protocol in the semi-honest two-party setting, which is able to be seamlessly integrated into …
QuietOT: Lightweight Oblivious Transfer with a Public-Key Setup
Oblivious Transfer (OT) is at the heart of secure computation and is a foundation for many
applications in cryptography. Over two decades of work have led to extremely efficient …
applications in cryptography. Over two decades of work have led to extremely efficient …