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Aftab Khan

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Multi-stage Attack Detection and Prediction Using Graph Neural Networks: An IoT Feasibility Study

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Apr 28, 2024
Hamdi Friji, Ioannis Mavromatis, Adrian Sanchez-Mompo, Pietro Carnelli, Alexis Olivereau, Aftab Khan

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Past, Present, Future: A Comprehensive Exploration of AI Use Cases in the UMBRELLA IoT Testbed

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Feb 01, 2024
Peizheng Li, Ioannis Mavromatis, Aftab Khan

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Mitigating System Bias in Resource Constrained Asynchronous Federated Learning Systems

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Feb 01, 2024
Jikun Gao, Ioannis Mavromatis, Peizheng Li, Pietro Carnelli, Aftab Khan

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FROST: Towards Energy-efficient AI-on-5G Platforms -- A GPU Power Capping Evaluation

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Oct 17, 2023
Ioannis Mavromatis, Stefano De Feo, Pietro Carnelli, Robert J. Piechocki, Aftab Khan

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Federated Deep Learning for Intrusion Detection in IoT Networks

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Jun 07, 2023
Othmane Belarbi, Theodoros Spyridopoulos, Eirini Anthi, Ioannis Mavromatis, Pietro Carnelli, Aftab Khan

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FLARE: Detection and Mitigation of Concept Drift for Federated Learning based IoT Deployments

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May 15, 2023
Theo Chow, Usman Raza, Ioannis Mavromatis, Aftab Khan

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Hierarchical and Decentralised Federated Learning

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Apr 28, 2023
Omer Rana, Theodoros Spyridopoulos, Nathaniel Hudson, Matt Baughman, Kyle Chard, Ian Foster, Aftab Khan

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Toward Multi-Service Edge-Intelligence Paradigm: Temporal-Adaptive Prediction for Time-Critical Control over Wireless

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Dec 12, 2022
Adnan Aijaz, Nan Jiang, Aftab Khan

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Demo: LE3D: A Privacy-preserving Lightweight Data Drift Detection Framework

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Nov 18, 2022
Ioannis Mavromatis, Aftab Khan

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LE3D: A Lightweight Ensemble Framework of Data Drift Detectors for Resource-Constrained Devices

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Nov 18, 2022
Ioannis Mavromatis, Adrian Sanchez-Mompo, Francesco Raimondo, James Pope, Marcello Bullo, Ingram Weeks, Vijay Kumar, Pietro Carnelli, George Oikonomou, Theodoros Spyridopoulos, Aftab Khan

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