A Study of Computational Trust Models in Cloud Security

A Study of Computational Trust Models in Cloud Security

Vaishali Ravindra Thakare, John Singh K
Copyright: © 2021 |Pages: 11
DOI: 10.4018/IJGHPC.2021070101
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The interest in cloud computing and its techniques are gaining exponentially in IT industries because of its cost-effective architecture and services. However, these flexible services of cloud bring many security and privacy challenges due to loss of control over the data. This paper focuses on an analysis of various computational trust models in cloud security environment. The computational trust models that are used to build secure cloud architectures are not available in a blended fashion to overcome security and privacy challenges. The paper aims to contribute to the literature review to assist researchers who are striving to contribute in this area. The main objective of this review is to identify and analyse the recently published research topics related to trust models and trust mechanisms for cloud with regard to research activity and proposed approaches. The future work is to design a trust mechanism for cloud security models to achieve the higher level of security.
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1. Motivation And Background

Cloud computing applications majorly provides heterogeneous platform environment for interactions and to provide different kinds of services on demand scale. Among all cloud services (Rahman et al., 2017; Somu et al., 2018) provided by cloud service provider, information sharing and data storage mechanisms are crucial. Cloud is treated as a semi trusted third party, it is very challenging to achieve fully trust of CSP while dealing with each other (Bui & Lee, 2016). One popular technique for estimating trust is based on past experience with particular agent. This technique is nothing but giving feedback of interaction between two parties and kind of services received by requester from provider (Somu et al., 2018; Yan et al., 2016). This technique decides, whether to interact with the same provider in future or not. So this is one of the technique to find out trustworthiness with provider and requester. Naturally, direct experience is the most reliable and personalized information for trust assessment. However, in large network (Lingam et al., 2018), open platforms like online social networks, straight experience is not desirable every time.

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