Dynamic Risk Access Control Model for Cloud Platform

摘要

In cloud environment, the traditional risk access control model cannot match rules dynamically and the risk values are insensitive for access requests. This paper proposed a cloud platform dynamic risk access control model (CPDAC) to solve the above problems. Firstly, the attribute-based access control model was improved by introducing the event calculus mechanism, and then the dynamic rule-matching module was constructed in the CPDAC. Secondly, based on programming regression (PR), the risk-evaluation-index weight distribution module was designed, and the risk assessment module with high sensitive value to access requests was constructed. Experimental results show that CPDAC is effective and feasible; in addition, the model is better in real-time and dynamic than other existing models.