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010   $a3-030-62746-2
024 7 $a10.1007/978-3-030-62746-1
035   $a(CKB)4100000011558813
035   $a(MiAaPQ)EBC6384943
035   $a(DE-He213)978-3-030-62746-1
035   $a(PPN)252504496
035   $a(EXLCZ)994100000011558813
100   $a20201104d2021      u|         0
101 0 $aeng
135   $aurnn#008mamaa
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 14$aThe 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy $eSPIoT-2020, Volume 2 /$fedited by John MacIntyre, Jinghua Zhao, Xiaomeng Ma
205   $a1st ed. 2021.
210   $cSpringer International Publishing$d2021
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2021.
215   $a1 online resource (XXXII, 863 p. 222 illus., 128 illus. in color.)
225 1 $aAdvances in Intelligent Systems and Computing,$x2194-5365 ;$v1283
300   $aIncludes index.
311 1 $a3-030-62745-4 
311   $a3-030-62745-4 
330   $aThis book presents the proceedings of The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIoT-2020), held in Shanghai, China, on November 6, 2020. Due to the COVID-19 outbreak problem, SPIoT-2020 conference was held online by Tencent Meeting. It provides comprehensive coverage of the latest advances and trends in information technology, science and engineering, addressing a number of broad themes, including novel machine learning and big data analytics methods for IoT security, data mining and statistical modelling for the secure IoT and machine learning-based security detecting protocols, which inspire the development of IoT security and privacy technologies. The contributions cover a wide range of topics: analytics and machine learning applications to IoT security; data-based metrics and risk assessment approaches for IoT; data confidentiality and privacy in IoT; and authentication and access control for data usage in IoT. Outlining promising future research directions, the book is a valuable resource for students, researchers and professionals and provides a useful reference guide for newcomers to the IoT security and privacy field.
410  0$aAdvances in Intelligent Systems and Computing,$x2194-5365 ;$v1283
606   $aEngineering?Data processing
606   $aCooperating objects (Computer systems)
606   $aComputational intelligence
606   $aMachine learning
606   $aBig data
606   $aData Engineering
606   $aCyber-Physical Systems
606   $aComputational Intelligence
606   $aMachine Learning
606   $aBig Data
615  0$aEngineering?Data processing.
615  0$aCooperating objects (Computer systems).
615  0$aComputational intelligence.
615  0$aMachine learning.
615  0$aBig data.
615 14$aData Engineering.
615 24$aCyber-Physical Systems.
615 24$aComputational Intelligence.
615 24$aMachine Learning.
615 24$aBig Data.
676   $a004.678
702   $aZhao$b Jinghua
702   $aMa$b Xiaomeng
702   $aMcIntyre$b John$f1916-2005,
712 12$aInternational Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy.
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bUtOrBLW
906   $aBOOK
912   $a9910863143603321
996   $aThe 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy$94166894
997   $aUNINA