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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…
Differential Privacy for Secure Machine Learning in Healthcare IoT-Cloud Systems
N Mangala, Murtaza Rangwala, S Aishwarya +5
Healthcare has become exceptionally sophisticated, as wearables and connected medical devices revolutionize remote patient monitoring, emergency response, medication management, di…
On the Generation of Phononic Frequency Combs Using Defect Modes of Phononic Crystals
Suhas Suresh Bharadwaj, Murtaza Rangwala, Adarsh Ganesan
This paper proposes a method for generating phononic frequency combs (PFCs) using defect-localized modes in a two-dimensional hexagonal phononic crystal. Localized vibration modes…
Screen Before You Fetch: Compressed Byzantine Screening for Decentralized Learning on the Edge-Cloud Continuum
Murtaza Rangwala, Farag Azzedin, Richard O. Sinnott +1
In decentralized federated learning, Byzantine-robust defenses filter neighbors by model similarity, but only after receiving each neighbor's full model. On constrained edge uplink…
Blockchain-Enabled Federated Learning
Murtaza Rangwala, KR Venugopal, Rajkumar Buyya
Blockchain-enabled federated learning (BCFL) addresses fundamental challenges of trust, privacy, and coordination in collaborative AI systems. This chapter provides comprehensive a…
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…