855 citations · 3.9k across the 142 of their papers we have counts for
5 papers · 1 filter
Hawk: Accurate and Fast Privacy-Preserving Machine Learning Using Secure Lookup Table Computation
Hamza Saleem, Amir Ziashahabi, Muhammad Naveed +1
Training machine learning models on data from multiple entities without direct data sharing can unlock applications otherwise hindered by business, legal, or ethical constraints. I…
Byzantine-Resilient Secure Federated Learning
Jinhyun So, Basak Guler, A. Salman Avestimehr
Secure federated learning is a privacy-preserving framework to improve machine learning models by training over large volumes of data collected by mobile users. This is achieved th…
Coded Merkle Tree: Solving Data Availability Attacks in Blockchains
Mingchao Yu, Saeid Sahraei, Songze Li +3
In this paper, we propose coded Merkle tree (CMT), a novel hash accumulator that offers a constant-cost protection against data availability attacks in blockchains, even if the maj…
INTERPOL: Information Theoretically Verifiable Polynomial Evaluation
Saeid Sahraei, A. Salman Avestimehr
We study the problem of verifiable polynomial evaluation in the user-server and multi-party setups. We propose {INTERPOL}, an information-theoretically verifiable algorithm that al…
PolyShard: Coded Sharding Achieves Linearly Scaling Efficiency and Security Simultaneously
Songze Li, Mingchao Yu, Chien-Sheng Yang +3
Today's blockchain designs suffer from a trilemma claiming that no blockchain system can simultaneously achieve decentralization, security, and performance scalability. For current…