Unique explainable federated learning approach for detecting model poisoning attacks to secure systems.

Muhammad Asad 0009 Information Technology University of the Punjab, Lahore, Pakistan Muhammad Asad Muhammad Asad 0001 King's College London, UK Imagination Technologies, Kings Langley, UK City University of London, UK University of Sheffield, UK https://masad.ml/ https://scholar.google.com/citations?user=SUS0SHIAAAAJ https://orcid.org/0000-0002-3672-2414 Muhammad Asad 0002 University of Tokyo, Department of Creative Informatics, Japan Nagoya Institute of Technology, Department of Computer Science, Japan Dalian University of Technology, China https://sites.google.com/view/asadhijaz/home https://orcid.org/0000-0003-0036-1714 https://www.wikidata.org/entity/Q96680867 https://ieeexplore.ieee.org/author/37088876025 Muhammad Asad 0003 National University of Sciences and Technology, School of Electrical Engineering and Computer Science, Islamabad, Pakistan aeroLiFi GmbH, Wessling, Germany Iqra University, Islamabad, Pakistan https://dl.acm.org/profile/99659369522 https://orcid.org/0000-0003-1186-3525 https://ieeexplore.ieee.org/author/38528022300 Muhammad Asad 0004 International Islamic University, Islamabad, Pakistan Muhammad Asad 0005 FAST National University of Computer and Emerging Sciences, Department of Computer Science, Karachi, Pakistan Muhammad Asad 0006 National University of Computer and Emerging Sciences, Department of Computer Sciences, Islamabad, Pakistan Muhammad Asad 0007 Ghulam Ishaq Khan Institute of Engineering Sciences and Technology, Topi, Pakistan Muhammad Asad 0008 Air University, Pakistan https://orcid.org/0000-0003-1119-646X

Muhmmad Fizan Alaa Awad Abdellatif Muhammad Asad 0009 Muhammad Zubair 0002 Bin Ni Bin Xu Xuefeng Liu Jichuan Xiong Muhammad Qasim Mehmood Unique explainable federated learning approach for detecting model poisoning attacks to secure systems. 1021 2025 December 28 Clust. Comput. 16 https://doi.org/10.1007/s10586-025-05695-1 db/journals/cluster/cluster28.html#FizanAAZNXLXM25 streams/journals/cluster

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