LEADER 01793nam  2200385 i 4500001    99125540620106421
005    20210417131657.0
006    m     o  d |
007    cr nn 008mamaa
008    210417s2021    sz      o     001 0 eng d
020    3-030-62743-8
024 7  10.1007/978-3-030-62743-0 |2doi
035    (CKB)4100000011558812
035    (MiAaPQ)EBC6384536
035    (DE-He213)978-3-030-62743-0
035    (PPN)25250450X
035    (EXLCZ)994100000011558812
040    MiAaPQ |beng |erda |epn |cMiAaPQ |dMiAaPQ
050  4 TA345 |b.A12 2021
072  7 UN |2bicssc
072  7 COM018000 |2bisacsh
072  7 UN |2thema
072  7 TB |2thema
082 0  620.00285 |223
245 04 The 2020 international conference on machine learning and big data analytics for IoT security and privacy. |pSPIoT-2020. |nVolume 1 / |cJohn MacIntyre, Jinghua Zhao, Xiaomeng Ma, editors.
250    1st ed. 2021.
264  1 Cham, Switzerland : |bSpringer, |c[2021]
264  4  |c2021
300    1 online resource (XXXI, 884 p. 221 illus., 150 illus. in color.)
336    text |btxt |2rdacontent
337    computer |bc |2rdamedia
338    online resource |bcr |2rdacarrier
490 1  Advances in intelligent systems and computing ; |vVolume 1282
520    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.
588    Description based on print version record.
500    Includes index.
650  0 Engineering |xData processing.
776     |z3-030-62742-X
797 2  ebrary
700 1  MacIntyre, J. D. |q(John D.), |eeditor.
700 1  Zhao, Jinghua, |eeditor.
700 1  Ma, Xiaomeng, |eeditor.
830  0 Advances in intelligent systems and computing ; |vVolume 1282.
906    BOOK