國立高雄大學圖資館 |

語系: 繁體中文

說明(常見問題)

圖資館首頁

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

The 2020 International Conference on...

(1998 :)

The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and PrivacySPIoT-2020.Volume 1 /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacyedited by John MacIntyre, Jinghua Zhao, Xiaomeng Ma.
其他題名:	SPIoT-2020.
其他題名:	SPIoT-2020
其他作者:	MacIntyre, John.
團體作者:
出版者:	Cham :Springer International Publishing :2021.
面頁冊數:	xxxi, 884 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Internet of thingsCongresses.Security measures
電子資源:	https://doi.org/10.1007/978-3-030-62743-0
ISBN:	9783030627430$q(electronic bk.)

The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and PrivacySPIoT-2020.Volume 1 /
The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and PrivacySPIoT-2020.Volume 1 /[electronic resource] :SPIoT-2020edited by John MacIntyre, Jinghua Zhao, Xiaomeng Ma. - Cham :Springer International Publishing :2021. - xxxi, 884 p. :ill., digital ;24 cm. - Advances in intelligent systems and computing,v.12822194-5357 ;. - Advances in intelligent systems and computing ;176..

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.

ISBN: 9783030627430$q(electronic bk.)

Standard No.: 10.1007/978-3-030-62743-0doiSubjects--Topical Terms:

773751
Internet of things
--Security measures--Congresses.

LC Class. No.: TK5105.8857 / .S65 2020

Dewey Class. No.: 004.678

The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and PrivacySPIoT-2020.Volume 1 /
LDR:02447nmm a2200349 a 4500 001 595967
003 DE-He213
005 20201103064047.0
006 m d
007 cr nn 008maaau
008 211013s2021 sz s 0 eng d
020 $a 9783030627430$q(electronic bk.)
020 $a 9783030627423$q(paper)
024 7 $a 10.1007/978-3-030-62743-0 $2 doi
035 $a 978-3-030-62743-0
040 $a GP $c GP $e rda
041 0 $a eng
050 4 $a TK5105.8857 $b .S65 2020
072 7 $a UN $2 bicssc
072 7 $a COM018000 $2 bisacsh
072 7 $a UN $2 thema
072 7 $a TB $2 thema
082 0 4 $a 004.678 $2 23
090 $a TK5105.8857 $b .S758 2020
111 2 $n (3rd : $d 1998 : $c Amsterdam, Netherlands) $3 194767
245 1 4 $a The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy $h [electronic resource] : $b SPIoT-2020. $n Volume 1 / $c edited by John MacIntyre, Jinghua Zhao, Xiaomeng Ma.
246 3 $a SPIoT-2020
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2021.
300 $a xxxi, 884 p. : $b ill., digital ; $c 24 cm.
490 1 $a Advances in intelligent systems and computing, $x 2194-5357 ; $v v.1282
520 $a 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.
650 0 $a Internet of things $x Security measures $v Congresses. $3 773751
650 0 $a Computer networks $x Security measures $v Congresses. $3 243786
650 1 4 $a Data Engineering. $3 839346
650 2 4 $a Cyber-physical systems, IoT. $3 836359
650 2 4 $a Computational Intelligence. $3 338479
650 2 4 $a Machine Learning. $3 833608
650 2 4 $a Big Data. $3 760530
700 1 $a MacIntyre, John. $3 841411
700 1 $a Zhao, Jinghua. $3 619010
700 1 $a Ma, Xiaomeng. $3 888544
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer Nature eBook
830 0 $a Advances in intelligent systems and computing ; $v 176. $3 567349
856 4 0 $u https://doi.org/10.1007/978-3-030-62743-0
950 $a Intelligent Technologies and Robotics (SpringerNature-42732)