Construction of Cloud ERP Security Evaluation Index System Based on Text Mining
The aim of this study is to investigate and discuss the potential security issues arising from the deployment of the Cloud Enterprise Resource Planning system, and to propose a perfect and standard set of security evaluation index system for Cloud ERP security issues. Considering the issues which may be inherent in the conventional Enterprise Resource Planning systems and new ones brought by Cloud Computing, Cloud Platform, Cloud ERP, we use text mining technology to mine the related standard files in this paper. Since the standard literature is based on the comprehensive results of technology, science and practice, its characteristics of standardization, objectivity and validity also ensure the effectiveness and applicability of indicators. By using NLP methods, we construct a Cloud ERP security evaluation index system consisting of five parts: evaluation method security, information access security, data security, management security and others. The entropy method is used to assign weights for the Cloud ERP security evaluation index system, which is more scientific and rational and the method moderates the lack of objectivity caused by traditional evaluation methods which over-relies on evaluators. By analyzing cases of Cloud ERP collected in various application reports and research papers, we improve our system and find that compared to other evaluation systems, our system can evaluate the security of Cloud ERP more comprehensively.