TY  - GEN
N2  - 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.
DO  - 10.1007/978-3-030-89511-2
DO  - doi
AB  - 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.
T1  - The 2021 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy :SPIoT-2021.
DA  - [2022]
CY  - Cham, Switzerland :
AU  - Macintyre, John.
AU  - Zhao, Jinghua.
AU  - Ma, Xiaomeng.
VL  - v. 98
CN  - TK5105.8857
PB  - Springer,
PP  - Cham, Switzerland :
PY  - [2022]
N1  - Includes author index.
ID  - 1442642
KW  - Internet of things
KW  - Computer networks
KW  - Internet des objets
KW  - Réseaux d'ordinateurs
SN  - 9783030895112
SN  - 3030895114
TI  - The 2021 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy :SPIoT-2021.
LK  - https://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-030-89511-2
UR  - https://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-030-89511-2
ER  -