6 papers
Detecting Masquerade Attacks in Controller Area Networks Using Graph Machine Learning
William Marfo, Pablo Moriano, Deepak K. Tosh +1
Modern vehicles rely on a myriad of electronic control units (ECUs) interconnected via controller area networks (CANs) for critical operations. Despite their ubiquitous use and rel…
Friction-Scaled Vibrotactile Feedback for Real-Time Slip Detection in Manipulation using Robotic Sixth Finger
Naqash Afzal, Basma Hasanen, Lakmal Seneviratne +2
The integration of extra-robotic limbs/fingers to enhance and expand motor skills, particularly for grasping and manipulation, possesses significant challenges. The grasping perfor…
Federated Learning for Efficient Condition Monitoring and Anomaly Detection in Industrial Cyber-Physical Systems
William Marfo, Deepak K. Tosh, Shirley V. Moore
Detecting and localizing anomalies in cyber-physical systems (CPS) has become increasingly challenging as systems grow in complexity, particularly due to varying sensor reliability…
Network Anomaly Detection in Distributed Edge Computing Infrastructure
William Marfo, Enrique A. Rico, Deepak K. Tosh +1
As networks continue to grow in complexity and scale, detecting anomalies has become increasingly challenging, particularly in diverse and geographically dispersed environments. Tr…
Efficient Client Selection in Federated Learning
William Marfo, Deepak K. Tosh, Shirley V. Moore
Federated Learning (FL) enables decentralized machine learning while preserving data privacy. This paper proposes a novel client selection framework that integrates differential pr…
Adaptive Client Selection in Federated Learning: A Network Anomaly Detection Use Case
William Marfo, Deepak K. Tosh, Shirley V. Moore
Federated Learning (FL) has become a widely used approach for training machine learning models on decentralized data, addressing the significant privacy concerns associated with tr…