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Smart city article details

Title	Machine Learning Based Security For Smart Cities
ID_Doc	35944
Authors	Amaizu G.C.; Lee J.-M.; Kim D.-S.
Year	2022
Published	APCC 2022 - 27th Asia-Pacific Conference on Communications: Creating Innovative Communication Technologies for Post-Pandemic Era
DOI	http://dx.doi.org/10.1109/APCC55198.2022.9943712
Abstract	The proliferation and wide usage of the Internet of Things (IoT) and related information and communication technologies (ICT) have led to the emergence of smart cities which comprises ubiquitous sensors, and heterogeneous network architectures. These cities are capable of relaying real-time information about the world which can then be used to improve the Qualify of Life (QoL). However, due to the unprecedented access to the city and personal data by smart city applications, there is an increase in both security and privacy threat. In this study, we propose a stacked generalization machine learning algorithm for the detection of cyberattacks in a smart city. The algorithm was tested using datasets from various smart city infrastructures. Simulation results show a high detection accuracy.
Author Keywords	Artificial Intelligence; IoT; Machine Learning; Security; Smart City

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