Privacy Preserving Blockchain Technique to Achieve Secure and Reliable Sharing of IoT Data
Bao Le Nguyen1, E. Laxmi Lydia2, Mohamed Elhoseny3, Irina V. Pustokhina4, Denis A. Pustokhin5, Mahmoud Mohamed Selim6, Gia Nhu Nguyen7, 8, K. Shankar9, *
1 Faculty of Information Technology, Duy Tan University, Da Nang, 550000, Vietnam.
2 Computer Science and Engineering, Vignan’s Institute of Information Technology, Visakhapatnam, 530049, India.
3 Faculty of Computers and Information, Mansoura University, Mansoura, 35516, Egypt.
4 Department of Entrepreneurship and Logistics, Plekhanov Russian University of Economics, Moscow, 115093, Russia.
5 Department of Logistics, State University of Management, Moscow, 109542, Russia.
6 Department of Mathematics, College of Science & Humanities in Alaflaj, Prince Sattam bin Abdulaziz University, Alaflaj, 16278, Saudi Arabia.
7 Graduate School, Duy Tan University, Da Nang, 550000, Vietnam.
8 Faculty of Information Technology, Duy Tan University, Da Nang, 550000, Vietnam.
9 Department of Computer Applications, Alagappa University, Karaikudi, 630003, India.
* Corresponding Author: K. Shankar. Email: .
Computers, Materials & Continua 2020, 65(1), 87-107. https://doi.org/10.32604/cmc.2020.011599
Received 18 May 2020; Accepted 15 July 2020; Issue published 23 July 2020
Abstract
In present digital era, an exponential increase in Internet of Things (IoT)
devices poses several design issues for business concerning security and privacy. Earlier
studies indicate that the blockchain technology is found to be a significant solution to
resolve the challenges of data security exist in IoT. In this view, this paper presents a new
privacy-preserving Secure Ant Colony optimization with Multi Kernel Support Vector
Machine (ACOMKSVM) with Elliptical Curve cryptosystem (ECC) for secure and
reliable IoT data sharing. This program uses blockchain to ensure protection and integrity
of some data while it has the technology to create secure ACOMKSVM training
algorithms in partial views of IoT data, collected from various data providers. Then, ECC
is used to create effective and accurate privacy that protects ACOMKSVM secure
learning process. In this study, the authors deployed blockchain technique to create a
secure and reliable data exchange platform across multiple data providers, where IoT data
is encrypted and recorded in a distributed ledger. The security analysis showed that the
specific data ensures confidentiality of critical data from each data provider and protects
the parameters of the ACOMKSVM model for data analysts. To examine the
performance of the proposed method, it is tested against two benchmark dataset such as
Breast Cancer Wisconsin Data Set (BCWD) and Heart Disease Data Set (HDD) from
UCI AI repository. The simulation outcome indicated that the ACOMKSVM model has
outperformed all the compared methods under several aspects.
Keywords
Cite This Article
B. Le Nguyen, E. Laxmi Lydia, M. Elhoseny, I. V. Pustokhina, D. A. Pustokhin
et al., "Privacy preserving blockchain technique to achieve secure and reliable sharing of iot data,"
Computers, Materials & Continua, vol. 65, no.1, pp. 87–107, 2020.
Citations