3 papers
cs.CR2026
Securing LLMs in the Wild: Privacy and Security Challenges at the Edge
Ren-Yi Huang, Mingchen Li, Dumindu Samaraweera +1
Large Language Models (LLMs) are rapidly moving from research settings into the wild, deployed on enterprise infrastructure, personal devices, and edge platforms. While cloud deplo…
cs.CR2025
Advancing Practical Homomorphic Encryption for Federated Learning: Theoretical Guarantees and Efficiency Optimizations
Ren-Yi Huang, Dumindu Samaraweera, Prashant Shekhar +1
Federated Learning (FL) enables collaborative model training while preserving data privacy by keeping raw data locally stored on client devices, preventing access from other client…
cs.CR2025
Secure Distributed Learning for CAVs: Defending Against Gradient Leakage with Leveled Homomorphic Encryption
Muhammad Ali Najjar, Ren-Yi Huang, Dumindu Samaraweera +1
Federated Learning (FL) enables collaborative model training across distributed clients without sharing raw data, making it a promising approach for privacy-preserving machine lear…