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Integrating internet-of-things with the power of cloud computing and the intelligence of big Data analytics- a three layered approach

Khorshed, Md Tanzim, Sharma, Neeraj A., Kumar, Kunal, Prasad, Mishal, Ali, A. B. M. Shawkat and Xiang, Yang 2015, Integrating internet-of-things with the power of cloud computing and the intelligence of big Data analytics- a three layered approach, in APWC on CSE 2015: Proceedings of the Asia-Pacific Computer Science and Engineering 2015 World Congress, IEEE, Piscataway, N.J., pp. 1-8, doi: 10.1109/APWCCSE.2015.7476124.

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Title Integrating internet-of-things with the power of cloud computing and the intelligence of big Data analytics- a three layered approach
Author(s) Khorshed, Md Tanzim
Sharma, Neeraj A.
Kumar, Kunal
Prasad, Mishal
Ali, A. B. M. Shawkat
Xiang, YangORCID iD for Xiang, Yang orcid.org/0000-0001-5252-0831
Conference name Asia-Pacific Computer Science and Engineering. World Congress (2nd : 2015 : Nadi, Fiji)
Conference location Nadi, Fiji
Conference dates 2-4 Dec. 2015
Title of proceedings APWC on CSE 2015: Proceedings of the Asia-Pacific Computer Science and Engineering 2015 World Congress
Editor(s) [Unknown]
Publication date 2015
Conference series Asia-Pacific Computer Science and Engineering World Congress
Start page 1
End page 8
Total pages 8
Publisher IEEE
Place of publication Piscataway, N.J.
Keyword(s) internet of things
IoT
cloud computing
big data
Hadoop
machine learning
cyber-attack
network security
Summary This paper is written through the vision on integrating Internet-of-Things (IoT) with the power of Cloud Computing and the intelligence of Big Data analytics. But integration of all these three cutting edge technologies is complex to understand. In this research we first provide a security centric view of three layered approach for understanding the technology, gaps and security issues. Then with a series of lab experiments on different hardware, we have collected performance data from all these three layers, combined these data together and finally applied modern machine learning algorithms to distinguish 18 different activities and cyber-attacks. From our experiments we find classification algorithm RandomForest can identify 93.9% attacks and activities in this complex environment. From the existing literature, no one has ever attempted similar experiment for cyber-attack detection for IoT neither with performance data nor with a three layered approach.
ISBN 9781509007134
Language eng
DOI 10.1109/APWCCSE.2015.7476124
Field of Research 080303 Computer System Security
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category E1 Full written paper - refereed
ERA Research output type E Conference publication
Copyright notice ©2015, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30084609

Document type: Conference Paper
Collection: School of Information Technology
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