Deep Learning Approaches for Security Threats in IoT Environm... - 9781119884149

Deep Learning Approaches for Security Threats in IoT EnvironmentsAuthor(s): Mohamed Abdel-Basset, Nour Moustafa, Hossam Hawash\nFormat: Hardback\nPublisher: John Wiley & Sons Inc, United States\nImprint: Wiley-IEEE Press\nISBN-13: 9781119884149, 978-1119884149\nSynopsis\nDeep Learning Approaches for Security Threats in IoT Environments An expert discussion of the application of deep learning methods in the IoT security environment In Deep Learning Approaches for Security Threats in IoT Environments, a team of distinguished cybersecurity educators deliver an insightful and robust exploration of how to approach and measure the security of Internet-of-Things (IoT) systems and networks. In this book, readers will examine critical concepts in artificial intelligence (AI) and IoT, and apply effective strategies to help secure and protect IoT networks. The authors discuss supervised, semi-supervised, and unsupervised deep learning techniques, as well as reinforcement and federated lear.