The 2021 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy
SPIoT-2021 Volume 1
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Beschreibung
This book presents the proceedings of the 2020 2nd International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIoT-2021), online conference, on 30 October 2021. 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.
This book presents the proceedings of the 2020 2nd International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIoT-2021), online conference, on 30 October 2021. 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.
Presents proceedings of the 2021 International Conference on Machine Learning and Big Data Analytics Contains the state-of-the-art in IoT security and privacy Written by experts in the field
Autor*in
John Macintyre
Themen in »The 2021 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy«
Novel Machine Learning and Big Data Analytics Methods Data Mining and Statistical Modelling for the Secure IoT Machine Learning Based Security Detecting Protocols Machine Learning Experiments, Test-beds and Prototyping Systems Analytics and Machine Learning Applications to IoT Security Data Based Metrics and Risk Assessment Approaches for IoT Data Confidentiality and Privacy in IoT Authentication and Access Control for Data Usage in IoT Data-driven Co-design of Communication Big Data Analytics/Deep Learning Edge/Fog Security Emerging Standards for IoT Security Big Data Analytics Smart City Cyber-Physical System Machine Learning