77 citations · 152 across the 6 of their papers we have counts for
4 papers · 1 filter
Dual Defense: Enhancing Privacy and Mitigating Poisoning Attacks in Federated Learning
Runhua Xu, Shiqi Gao, Chao Li +2
Federated learning (FL) is inherently susceptible to privacy breaches and poisoning attacks. To tackle these challenges, researchers have separately devised secure aggregation mech…
TAPFed: Threshold Secure Aggregation for Privacy-Preserving Federated Learning
Runhua Xu, Bo Li, Chao Li +3
Federated learning is a computing paradigm that enhances privacy by enabling multiple parties to collaboratively train a machine learning model without revealing personal data. How…
Revisiting Secure Computation Using Functional Encryption: Opportunities and Research Directions
Runhua Xu, James Joshi
Increasing incidents of security compromises and privacy leakage have raised serious privacy concerns related to cyberspace. Such privacy concerns have been instrumental in the cre…
An Automatic Attribute Based Access Control Policy Extraction from Access Logs
Leila Karimi, Maryam Aldairi, James Joshi +1
With the rapid advances in computing and information technologies, traditional access control models have become inadequate in terms of capturing fine-grained, and expressive secur…