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云计算时代的到来，云的可信性越来越受到人们的关注，研究者提出了各种各样的模型和验证机制来保证云的可信。但是大多数研究工作仅仅关注可信模型和机制的设计与实现，很少关注如何检验可信机制的效果，尤其是有效性。本文提出了一种新颖的方法，通过计算可信机制减少的攻击危害，以及产生的性能代价来量化和评估云可信机制的有效性。然后针对周期性验证机制如何选择最佳检测周期的问题，提出了最佳检测周期预测机制，预测可能的最佳周期。模拟实验结果表明，本方法可以较为准确的量化可信机制的有效性，预测最佳检测周期以减少引入的性能代价。“,”With the advent of the cloud computing era, the problem of cloud trustiness takes more and more attention, and many models and mechanisms are proposed to audit or attest the trustiness of cloud and virtual machine. However, most research mainly concentrates in the design and implementation of model and the mechanism and takes less attention to assess the validity of the models and the mechanisms. In this paper, a novel method is proposed to quantify and assess the validity of trust models by calculating the attack damage reduced and the performance cost introduced by the trust mechanism. Then, for the periodic verification mechanism, the best detection cycle prediction mechanism is proposed to solve the issue of how to select the best detection cycle. The simulation experiments demonstrate that this method can quantify accuratly the effectiveness of turst mechanisms and predict the optimum detection cycle to reduce performance cost.