Abstract
This research proposes a cloud consumer trust model that focuses on decision making and the value of our data. The value consumers place on data plays a critical role in how consumers trust. The research was validated with a questionnaire and statistical power analysis. Few cloud trust models appear to be validated against real world data, and none, that we found, accomplish an a-priori statistical power analysis. Results indicated consumers were interested in data location, third party access and most surprisingly unbiased/expert organization recommendations were more important than family and friends recommendations.
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References
Marsh, S.P.: Formalising trust as a computational concept (1994)
Castelfranchi, C., Falcone, R.: Trust Theory: A Socio-Cognitive and Computational Model, vol. 18. Wiley, Hoboken (2010)
Pearl, J.: Bayesian networks (2011)
Sapienza, A., Falcone, R.: A Bayesian computational model for trust on information sources. In: WOA, pp. 50–55 (2016)
Wang, Y., Vassileva, J.: Bayesian network-based trust model. In: IEEE/WIC International Conference on WebIntelligence, 2003, WI 2003, Proceedings, pp. 372–378. IEEE (2003)
Wang, Y., Cahill, V., Gray, E., Harris, C., Liao, L.: Bayesian network based trust management. In: International Conference on Autonomic and Trusted Computing, pp. 246–257. Springer (2006)
Nielsen, M., Krukow, K., Sassone, V.: A Bayesian model for event-based trust. Electron. Notes Theor. Comput. Sci. 172, 499–521 (2007)
Melaye, D., Demazeau, Y.: Bayesian dynamic trust model. In: International Central and Eastern European Conference on Multi-agent Systems, pp. 480–489. Springer (2005)
Thirunarayan, K., Anantharam, P., Henson, C., Sheth, A.: Comparative trust management with applications: Bayesian approaches emphasis. Future Gener. Comput. Syst. 31, 182–199 (2014)
Kirkman, S., Newman, R.: A data movement policy framework for improving trust in the cloud using smart contracts and blockchains. In: 2018 IEEE International Conference on Cloud Engineering (IC2E), pp. 270–273. IEEE (2018)
Alsmadi, D., Prybutok, V.: Sharing and storage behavior via cloud computing: security and privacy in research and practice. Comput. Hum. Behav. 85, 218–226 (2018)
Burda, D., Teuteberg, F.: The role of trust and risk perceptions in cloud archiving: results from an empirical study. J. High Technol. Manage. Res. 25(2), 172–187 (2014)
Horvath, A.S., Agrawal, R.: Trust in cloud computing. In: SoutheastCon 2015, pp. 1–8. IEEE (2015)
Hsu, P.-F., Ray, S., Li-Hsieh, Y.-Y.: Examining cloud computing adoption intention, pricing mechanism, and deployment model. Int. J. Inf. Manage. 34(4), 474–488 (2014)
Cohen, J.: Statistical Power Analysis for the Behavioral Sciences, 2nd edn. Lawrence Erlbaum Associates, Mahwah (1988)
Kirkman, S., Newman, R.: Intercloud: a data movement policy DApp for managing trust in the cloud. In: 5th Annual Conference on Computational Science and Computational Intelligence (CSCI 2018), CSCI (2018)
Peck, R., Olsen, C., DeVore, J.L.: Introduction to Statistics and Data Analysis. Cengage Learning (2000)
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Kirkman, S., Newman, R. (2020). A Trust Model for Cloud: Results from a Survey. In: Arai, K., Bhatia, R., Kapoor, S. (eds) Proceedings of the Future Technologies Conference (FTC) 2019. FTC 2019. Advances in Intelligent Systems and Computing, vol 1069. Springer, Cham. https://doi.org/10.1007/978-3-030-32520-6_36
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DOI: https://doi.org/10.1007/978-3-030-32520-6_36
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