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Haedam Kim, Suhyun Park, Hyemin Hong, Jieun Park and Seongmin Kim
As the size of the IoT solutions and services market proliferates, industrial fields utilizing IoT devices are also diversifying. However, the proliferation of IoT devices, often intertwined with users? personal information and privacy, has led to a cont...
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David Naseh, Mahdi Abdollahpour and Daniele Tarchi
This paper explores the practical implementation and performance analysis of distributed learning (DL) frameworks on various client platforms, responding to the dynamic landscape of 6G technology and the pressing need for a fully connected distributed in...
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Gang Wang, Dong Liu, Chunrui Zhang and Teng Hu
This work has potential usages in cyber-attack detection in air-gapped internal networks that lack sufficient labeled data samples to build detection models for network attack activities.
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Lorenzo Ridolfi, David Naseh, Swapnil Sadashiv Shinde and Daniele Tarchi
With the advent of 6G technology, the proliferation of interconnected devices necessitates a robust, fully connected intelligence network. Federated Learning (FL) stands as a key distributed learning technique, showing promise in recent advancements. How...
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Yunqian Yu, Kun Tang and Yaqing Liu
Daily activity recognition between different smart home environments faces some challenges, such as an insufficient amount of data and differences in data distribution. However, a deep network requires a large amount of labeled data for training. Additio...
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Kaiyuan Jiang, Yutong Zhang, Haibin Wu, Aili Wang and Yuji Iwahori
Software systems are now ubiquitous and are used every day for automation purposes in personal and enterprise applications; they are also essential to many safety-critical and mission-critical systems, e.g., air traffic control systems, autonomous cars, ...
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