A Multi-Dimensional and Multi-Factor Trust Computation Framework for Cloud Services

Junejo

Abstract

In this paper, we propose a novel trust computation framework (TCF) for cloud services. Trust is computed by taking into consideration multi-dimensional quality of service (QoS) evidence and user feedback. Feedback provides ample evidence regarding the quality of experience (QoE) of cloud service users. However, in some cases, users may behave maliciously and report false feedback. Users can carry out collusion and Sybil attacks to slander/self-promote cloud services. Trust computed in such cases could be misleading and inaccurate. Evaluating the credibility of user feedback can help in not only preventing the collusion and Sybil attacks but also remunerating the affected cloud services. Despite the advantages of credibility evaluation, very few studies take into consideration feedback credibility and multi-dimensional evaluation criteria. Considering the limitations of existing studies, we propose a new TCF in which trust is computed by aggregating multi-dimensional evidence from QoS and QoE. We have used multi-dimensional QoS attributes to compute the objective trust of cloud services. The QoS attributes are divided into three dimensions, i.e., node profile, average resource consumption, and performance. The node profile of a cloud service is attributed to CPU frequency, memory size, and hard disk capacity. The average resource consumption is quantified based on the current CPU utilisation rate, current memory utilisation rate, current hard disk utilisation rate, and energy consumption. Moreover, the performance of a cloud service is measured by the average response time and task success ratio. Besides that, the credibility of feedback is evaluated to prevent the malicious behaviour of cloud users. Our results demonstrate the effectiveness of our proposed TCF in computing accurate trust in cloud services.

Citation

Junejo. (2022). A Multi-Dimensional and Multi-Factor Trust Computation Framework for Cloud Services. Electronics, https://doi.org/10.3390/electronics11131932

• Acceptance Date: Jun 19, 2022
• Publication Date: Jun 21, 2022
• Journal: Electronics
• Publisher: MDPI
• DOI: https://doi.org/10.3390/electronics11131932
• Keywords: cloud services; trust; objective trust; subjective trust; user feedback; regression; credibility; Sybil; collusion
• Publisher URL: https://www.mdpi.com/2079-9292/11/13/1932