Risk Factor Assessment Improvement for China's Cloud Computing Auditing Using a New Hybrid MADM Model

With the rapid growth of modern technology in all facets of trade and industry, traditional auditing systems can no longer meet today's ever-increasing technological requirements; contemporary auditing is in urgent need of straightforward and quick cloud computing services to meet the needs of auditors. In keeping with current trends, auditors must be provided with the means of using data and auditing information stored in cloud systems for more effcient and elastic auditing. However, the risks involved in cloud computing auditing are widespread and complex. Dimensions should be established, a mutually influential relationship used to delineate the influence weights of the dimensions and criteria should be determined. To this end, a Multiple Attribute Decision Making ( MADM) model can precisely solve multi-criteria problems simultaneously. Therefore, the main focus of this study is to determine how to assess and establish the best improvement strategies to achieve the aspiration level for cloud auditing risk factors, by using the opinions and practical experience of China's accounting experts, applied with a Decision-Making Trial and Evaluation Laboratory (DEMATEL) technique, DEMATEL-based ANP (DANP) and modified VIKOR method. The results provide cloud auditing risks with a knowledge-based understanding of the problem sources in order to establish the best improvement strategies for reducing risk-auditing performance gaps and attaining the aspiration levels. Based on the degree of impact of the dimensions/criteria on an Influence Network Relation Map (INRM), improvements should be prioritized as follows: system operations, technology risks, identity and access management and data protection.