Abstract
The Cloud computing paradigm provides numerous attractive services to customers such as the provision of the on-demand self-service, usage-based pricing, ubiquitous network access, transference of risk, and location independent resource sharing. However, the security of cloud computing, especially its data privacy, is a highly challengeable task. To address the data privacy issues, several mechanisms have been proposed that use the third party auditor (TPA) to ensure the integrity of outsourced data for the satisfaction of cloud users (CUs). However, the role of the TPA could be the potential security threat itself and can create new security vulnerabilities for the customer’s data. Moreover, the cloud service providers (CSPs) and the CUs could also be the adversaries while deteriorating the stored private data. As a result, the objective of this research is twofold. Our first research goal is to analyze the data privacy-preserving issues by identifying unique privacy requirements and presenting a supportable solution that eliminates the possible threats towards data privacy. Our second research goal is to develop the privacy-preserving model (PPM) to audit all the stakeholders in order to provide a relatively secure cloud computing environment. Specifically, the proposed model ensures the quality of service (QoS) of cloud services and detects potential malicious insiders in CSPs and TPAs. Furthermore, our proposed model provides a methodology to audit a TPA for minimizing any potential insider threats. In addition, CUs can use the proposed model to periodically audit the CSPs using the TPA to ensure the integrity of the outsourced data. For demonstrating and validating the performance, the proposed PPM is programmed in C++ and tested on GreenCloud with NS2 by applying merging processes. The experimental results help to identify the effectiveness, operational efficiency, and reliability of the CSPs. In addition, the results demonstrate the successful rate of handling the negative role of the TPA and determining the TPA’s malicious insider detection capabilities.
Highlights
Cloud computing is an emerging IT environment that has significantly transformed everyone’s vision of computing infrastructure, development models, and software distribution
Effectiveness of cloud service provider (CSP) In the first scenario, we investigate the effectiveness of the cloud service providers (CSPs) based on the provided services to cloud users (CUs)
To build a secure and efficient cloud computing environment, we extend and improve the existing CSP and third party auditor (TPA) security models by leveraging the properties into a single triangular data privacypreserving model to provide the auditing capability to all the key stakeholders
Summary
Cloud computing is an emerging IT environment that has significantly transformed everyone’s vision of computing infrastructure, development models, and software distribution. Cloud computing is anticipated as the generation high-tech paradigm for tomorrow’s promise [1] It provides several utilities as revolutionary gigantic paradigms where clients can remotely store valuable and confidential information as to avail from on-demand high quality computing resources [2]. Since the CUs do not have physical access to the outsourced data, it raises the question of data privacy protection in cloud computing, for users with very limited computing resources. Cloud services can be financially advantageous; there is no guarantee that the stored data will be secure and available at all times. If this continues to be an issue and is not thoroughly examined, the cloud computing environment may never reach its full potential
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