Title: Entropy-based classification of trust factors for cloud computing

Authors: Ankita Sharma; Puja Munjal; Hema Banati

Addresses: Jagan Institute of Management Studies, Guru Gobind Singh Indraprastha University (GGSIPU), Rohini, New Delhi, India ' Department of Computer Science, Sri Guru Tegh Bahadur Khalsa College, University of Delhi, New Delhi, India ' Department of Computer Science, Dyal Singh College, University of Delhi, New Delhi, India

Abstract: Cloud computing has now been introduced in organisations all around the globe. With the developing prevalence of grid and distributed computing, it has become incredibly important to maintain security and trust. Researchers have now begun concentrating on mining information in cloud computing and have begun distinguishing the basic factor of moral trust. Moral angles in the cloud rely upon the application and the present conditions. Data mining is a procedure for distinguishing the most significant data from a lot of irregular information. In this paper, a three phased methodology is adopted, involving machine learning techniques to discover the most important parameter on which trust is based in the cloud environment. The methodology was then implemented on data sets, proving privacy is the most important factor to calculate ethical trust in cloud computing. The results can be employed in real cloud environments to establish trust as service providers can now consider privacy as the main issue in this relatively new distributed computing environment.

Keywords: cloud computing; data mining; classification; decision tree; trust; entropy; multivariate regression.

DOI: 10.1504/IJGUC.2020.110909

International Journal of Grid and Utility Computing, 2020 Vol.11 No.6, pp.747 - 754

Received: 06 Jul 2019
Accepted: 26 Sep 2019
Published online: 01 Nov 2020 *

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