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Title	Using Artificial Intelligence To Defend Internet Of Things For Smart City Networks
ID_Doc	60482
Authors	Nunn A.; Prasad P.W.C.
Year	2024
Published	Lecture Notes in Electrical Engineering, 117 LNEE
DOI	http://dx.doi.org/10.1007/978-3-031-71773-4_21
Abstract	As these IoT devices have been embedded and operate within Smart City networks they are also open to vulnerabilities similar to other technologies, however, unlike other technologies, these IoT cannot run a defence in depth protective layer as these devices will run very specific niche software from vendors for their intended purpose. This leaves many of these IoT devices, which can operate power grids, control transit across the cityscape, and provide communications to its citizens or surveillance for protection, are at significant risk of exposure with the emergence of using Artificial Intelligence to enhance attack techniques and therefore would be predisposed to cyber-attacks. This research project explores concepts and proposes a framework for using Artificial Intelligence in combination with modern cyber defence strategies, the application of Machine Learning or Deep Learning to existing technical controls, such as an Intrusion Detection System, then using a Software-Defined Networking or Fog Computing as the delivery medium to overcome the resource limitations for a Smart City IoT network has significant potential. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
Author Keywords	Adversarial Retraining; Artificial intelligence; Deep Learning; Denial of; Internet of Things; Intrusion Detection System; Machine Learning; Machine Learning; Neural Networking; Software-Defined Networking

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