1 citations · 1 across the 6 of their papers we have counts for
7 papers
Model Multiplicity for Adversarial Detection in Small Language Model Training on Edge Devices
Stefan Behfar, Richard Mortier
The rise of edge-based machine learning has enabled distributed adaptation of language models across mobile and IoT devices, offering privacy preservation and real-time responsiven…
Robust Synchronisation for Federated Learning in The Face of Correlated Device Failure
Stefan Behfar, Richard Mortier
Probabilistic Synchronous Parallel (PSP) is a technique in distributed learning systems to reduce synchronization bottlenecks by sampling a subset of participating nodes per round.…
Cumulative Utility Parity for Fair Federated Learning under Intermittent Client Participation
Stefan Behfar, Richard Mortier
In real-world federated learning (FL) systems, client participation is intermittent, heterogeneous, and often correlated with data characteristics or resource constraints. Existing…
Analysis of Information Propagation in Ethereum Network Using Combined Graph Attention Network and Reinforcement Learning to Optimize Network Efficiency and Scalability
Stefan Kambiz Behfar, Jon Crowcroft
Blockchain technology has revolutionized the way information is propagated in decentralized networks. Ethereum plays a pivotal role in facilitating smart contracts and decentralize…
Towards Adaptive, Learning-Based Security in Decentralized Applications
Stefan Kambiz Behfar, Jon Crowcroft
Web3 systems expose a fundamentally different security landscape from centralized platforms, characterized by composability, pseudonymous identities, decentralized governance, and…
Architecture of Data Anomaly Detection-Enhanced Decentralized Expert System for Early-Stage Alzheimer's Disease Prediction
Stefan Kambiz Behfar, Qumars Behfar, Marzie Hosseinpour
Alzheimer's Disease is a global health challenge that requires early and accurate detection to improve patient outcomes. Magnetic Resonance Imaging (MRI) holds significant diagnost…
Probabilistic Sampling-Enhanced Temporal-Spatial GCN: A Scalable Framework for Transaction Anomaly Detection in Ethereum Networks
Stefan Kambiz Behfar, Jon Crowcroft
The rapid evolution of the Ethereum network necessitates sophisticated techniques to ensure its robustness against potential threats and to maintain transparency. While Graph Neura…