Title: Social internet of things using big data analytics and security aspects - a review

Authors: S. Deva Arul; Meenakshisundaram Iyapparaja

Addresses: School of Information Technology and Engineering, VIT University, Vellore, Tamil Nadu, India ' School of Information Technology and Engineering, VIT University, Vellore, Tamil Nadu, India

Abstract: The rapid development of technologies in today's world has become interesting that made millions of people to utilise the major advantages in it. Two main technologies that were emerging in modern society are big data and the social internet of things. Several researchers have studied and developed a major concept of using big data with SIoT and the security development of maintain a large amount of data. In this paper, deep survey regarding the concepts behind the big data analytics with the social internet of things (SIoT) was studied and analysed. Furthermore, the machine learning techniques that were used in previous works were analysed and comparisons of various methods are discussed. The performance comparison of various classifiers on different datasets is shown and SVM has more than 90% of accuracy when compared with other algorithms. KNN has 64% of accuracy which is lowest of any classifier than NB and NN.

Keywords: big data; social internet of things; SIoT; frequent itemset mining; FIM; machine learning.

DOI: 10.1504/EG.2020.105238

Electronic Government, an International Journal, 2020 Vol.16 No.1/2, pp.137 - 154

Received: 06 Mar 2019
Accepted: 31 May 2019
Published online: 22 Feb 2020 *

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