TY - GEN N2 - This book presents the proceedings of The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIoT-2020), held in Shanghai, China, on November 6, 2020. Due to the COVID-19 outbreak problem, SPIoT-2020 conference was held online by Tencent Meeting. It provides comprehensive coverage of the latest advances and trends in information technology, science and engineering, addressing a number of broad themes, including novel machine learning and big data analytics methods for IoT security, data mining and statistical modelling for the secure IoT and machine learning-based security detecting protocols, which inspire the development of IoT security and privacy technologies. The contributions cover a wide range of topics: analytics and machine learning applications to IoT security; data-based metrics and risk assessment approaches for IoT; data confidentiality and privacy in IoT; and authentication and access control for data usage in IoT. Outlining promising future research directions, the book is a valuable resource for students, researchers and professionals and provides a useful reference guide for newcomers to the IoT security and privacy field. DO - 10.1007/978-3-030-62743-0 DO - doi AB - This book presents the proceedings of The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIoT-2020), held in Shanghai, China, on November 6, 2020. Due to the COVID-19 outbreak problem, SPIoT-2020 conference was held online by Tencent Meeting. It provides comprehensive coverage of the latest advances and trends in information technology, science and engineering, addressing a number of broad themes, including novel machine learning and big data analytics methods for IoT security, data mining and statistical modelling for the secure IoT and machine learning-based security detecting protocols, which inspire the development of IoT security and privacy technologies. The contributions cover a wide range of topics: analytics and machine learning applications to IoT security; data-based metrics and risk assessment approaches for IoT; data confidentiality and privacy in IoT; and authentication and access control for data usage in IoT. Outlining promising future research directions, the book is a valuable resource for students, researchers and professionals and provides a useful reference guide for newcomers to the IoT security and privacy field. T1 - The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy :SPIoT-2020. AU - MacIntyre, J. D. AU - Zhao, Jinghua, AU - Ma, Xiaomeng, VL - volume 1282 CN - TK5105.8857 ID - 1432306 KW - Internet of things KW - Computer networks KW - Internet des objets KW - Réseaux d'ordinateurs SN - 9783030627430 SN - 3030627438 TI - The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy :SPIoT-2020. LK - https://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-030-62743-0 UR - https://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-030-62743-0 ER -