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Configuring a Trusted Cloud Service Model for Smart City Exploration Using Hybrid Intelligence

Configuring a Trusted Cloud Service Model for Smart City Exploration Using Hybrid Intelligence

Manash Sarkar, Soumya Banerjee, Youakim Badr, Arun Kumar Sangaiah
Copyright: © 2017 |Volume: 8 |Issue: 3 |Pages: 21
ISSN: 1941-6237|EISSN: 1941-6245|EISBN13: 9781522523017|DOI: 10.4018/IJACI.2017070101
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MLA

Sarkar, Manash, et al. "Configuring a Trusted Cloud Service Model for Smart City Exploration Using Hybrid Intelligence." IJACI vol.8, no.3 2017: pp.1-21. http://doi.org/10.4018/IJACI.2017070101

APA

Sarkar, M., Banerjee, S., Badr, Y., & Sangaiah, A. K. (2017). Configuring a Trusted Cloud Service Model for Smart City Exploration Using Hybrid Intelligence. International Journal of Ambient Computing and Intelligence (IJACI), 8(3), 1-21. http://doi.org/10.4018/IJACI.2017070101

Chicago

Sarkar, Manash, et al. "Configuring a Trusted Cloud Service Model for Smart City Exploration Using Hybrid Intelligence," International Journal of Ambient Computing and Intelligence (IJACI) 8, no.3: 1-21. http://doi.org/10.4018/IJACI.2017070101

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Abstract

Emerging research concerns about the authenticated cloud service with high performance of security and assuring trust for distributed clients in a smart city. Cloud services are deployed by the third-party or web-based service providers. Thus, security and trust would be considered for every layer of cloud architecture. The principle objective of cloud service providers is to deliver better services with assurance of trust about clients' information. Cloud's users recurrently face different security challenges about the use of sharable resources. It is really difficult for Cloud Service Provider for adapting varieties of security policies to sustain their enterprises' goodwill. To make an optimistic decision that would be better suitable to provide a trusted cloud service for users' in smart city. Statistical method known as Multivariate Normal Distribution is used to select different attributes of different security entities for developing the proposed model. Finally, fuzzy multi objective decision making and Bio-Inspired Bat algorithm are applied to achieve the objective.

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