Abstract
In cloud computing, dynamic storage of data generated by users, applications, tasks, workflows, etc. requires frequent access operations, so traditional encryption cannot be applied in this case. Considering the vulnerability of dynamic data, its protection needs to consider an efficient and dynamic security protection scheme. In data-oriented access control, the traditional approach is generally static policy matching, which cannot deal with emergencies and has the problem of privileged users. To solve this problem, this paper proposes a data-oriented risk-based access control model, which adds risk assessment to the traditional attribute-based access control and aims at the source of risk from three aspects: subject attribute, resource attribute, and environment attribute. A set of risk assessment indexes is proposed, and the calculation method of risk assessment is quantitatively analyzed by combining fuzzy consistency AHP analysis method, and finally, the realization of XACML is given. The validity of the proposed model is analyzed, and the carried out experimental analysis verifies its effectiveness. The proposed model benefits cloud data storage applications that require dynamic data storage, for example, medical/patient data storage.