2 papers
cs.CR2025
LATTEO: A Framework to Support Learning Asynchronously Tempered with Trusted Execution and Obfuscation
Abhinav Kumar, George Torres, Noah Guzinski +6
The privacy vulnerabilities of the federated learning (FL) paradigm, primarily caused by gradient leakage, have prompted the development of various defensive measures. Nonetheless,…
cs.CR2021
Off-chain Execution and Verification of Computationally Intensive Smart Contracts
Emrah Sariboz, Kartick Kolachala, Gaurav Panwar +2
We propose a novel framework for off-chain execution and verification of computationally-intensive smart contracts. Our framework is the first solution that avoids duplication of c…