A trusted evidence model for cloud platform

Lili Wu, Jing Zhan and Yong Zh

Abstract

Trusted evidence collection is an important content in the study of the cloud platform trustworthiness. Trusted evidence collection model should not only meet the description of cloud platform credible evidence, but also solve the problems of model expansion by the massive evidence instance on the cloud platform. Based on the characteristics of data in the cloud, such as huge amounts and diversity of usage scenarios, evidence sources, and service types, we proposed the definition of credibility and trusted evidence on the cloud platform, and put forward a customized model of trusted evidence. According to the different sources and properties of trusted evidence, the model can describes and stores credible evidence, and it provides an efficient method of data description and access for the subsequent remote attestation.