activity
20142026
most citedFheFL: Fully Homomorphic Encryption Friendly Privacy-Preserving Federated Learning with Byzantine Users

7 citations · 17 across the 11 of their papers we have counts for

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Showing 2025Show all

2 papers · 1 filter

cs.CR2025

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation

Charuka Herath, Yogachandran Rahulamathavan, Varuna De Silva +1

Federated Learning (FL) enables decentralized model training without sharing raw data, offering strong privacy guarantees. However, existing FL protocols struggle to defend against…

cs.CL2025

PLEX: Perturbation-free Local Explanations for LLM-Based Text Classification

Yogachandran Rahulamathavan, Misbah Farooq, Varuna De Silva

Large Language Models (LLMs) excel in text classification, but their complexity hinders interpretability, making it difficult to understand the reasoning behind their predictions.…