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Title	Deep Learning-Based Cyber Security Solutions For Smart-City: Application And Review
ID_Doc	17947
Authors	Bhardwaj T.; Upadhyay H.; Lagos L.
Year	2022
Published	Learning and Analytics in Intelligent Systems, 25
DOI	http://dx.doi.org/10.1007/978-3-030-85383-9_12
Abstract	This book chapter provides the readers hands-on experience about the deep learning algorithms and their use case for cyber security solutions in the smart city ecosystem. In this book chapter, the authors first describe the background about the smart city ecosystem, cyber security threats and deep learning algorithms. Subsequently, the authors describe the overview of popular architectures of deep learning algorithms with their applications for addressing various cyber security threats. In this study, the author talks about convolutional neural networks (CNNs), fully connected convolutional networks (FCNs), Recurrent Neural Network (RNN), Deep Belief Network (DBN), Boltzmann Machine, and Auto-encoders. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
Author Keywords	Cyber Security; Deep Learning Algorithms; Literature Review; Smart City

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