4 papers
Topology-Aware Differential Privacy in Hierarchical Federated Learning
Murtaza Rangwala, Richard O. Sinnott, Rajkumar Buyya
Hierarchical federated learning places regional aggregators between clients and the cloud, so a participant's update is observed only alongside its neighbours'. The concealment thi…
SketchGuard: Scaling Byzantine-Robust Decentralized Federated Learning via Sketch-Based Screening
Murtaza Rangwala, Farag Azzedin, Richard O. Sinnott +1
Byzantine-robust decentralized federated learning (DFL) protects peer-to-peer training from malicious clients. The dominant defenses rely on similarity-based filtering, in which ea…
Multi-Sourced, Multi-Agent Evidence Retrieval for Fact-Checking
Shuzhi Gong, Richard O. Sinnott, Jianzhong Qi +3
Misinformation spreading over the Internet poses a significant threat to both societies and individuals, necessitating robust and scalable fact-checking that relies on retrieving a…
Evidential Trust-Aware Model Personalization in Decentralized Federated Learning for Wearable IoT
Murtaza Rangwala, Richard O. Sinnott, Rajkumar Buyya
Decentralized federated learning (DFL) enables collaborative model training across edge devices without centralized coordination, offering resilience against single points of failu…