Abstract
Assessing trust of cloud providers is considered to be a key factor to discriminate between them, especially once dealing with Big Data. In this paper, we apply Multiple Linear Regression (MLR) to develop a trust model for processing Big Data over diverse Clouds. The model relies on MLR to predict trust score of different cloud service providers. Therefore, support selection of the trustworthiness provider. Trust is evaluated not only on evidenced information collected about cloud resources availability, but also on past experiences with the cloud provider, and the reputation collected from other users experienced with the same cloud services. We use cross validation to test the consistency of the estimated regression equation, and we found that the model can perfectly be used to predict the response variable trust. We also, use bootstrap scheme to evaluate the confidence intervals for each pair of variables used in building our trust model.
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El-Kassabi, H., Serhani, M.A., Bouhaddioui, C., Dssouli, R. (2018). Trust Assessment-Based Multiple Linear Regression for Processing Big Data Over Diverse Clouds. In: Belqasmi, F., Harroud, H., Agueh, M., Dssouli, R., Kamoun, F. (eds) Emerging Technologies for Developing Countries. AFRICATEK 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 206. Springer, Cham. https://doi.org/10.1007/978-3-319-67837-5_10
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DOI: https://doi.org/10.1007/978-3-319-67837-5_10
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