Research on Security Assessment of Cross Border Data Flow

Abstract

AbstractAt present, the trend of cross-border data flow is inevitable. Therefore, as the liquidity demand for cross-border data increases, the issues related to national security and the protection of personal data are gradually exposed. Due to the demand and cost problems, the domestic risk assessment only stays in the business scope of the company or enterprise. Even if the data processing process involves the data subject and data controller, the evaluation object is only for the data controller. In order to avoid risks, enterprises will conduct multiple risk assessments on data during the business execution cycle. Therefore, the domestic risk assessment model has the characteristics of a single process and multiple cycles. However, there are differences in use, scope, and characteristics between cross-border data risk assessment and domestic risk assessment. That’s why the general evaluation model can’t be directly applied to the cross-border process. Therefore, the purpose of this paper is to propose a multi process and multi cycle data security risk assessment model applicable to cross-border data. The two processes of domestic risk assessment and foreign cross-border process assessment are integrated in this article. Therefore, the analysis of risk factors is also based on these two perspectives. In addition, common risk assessment methods such as comprehensive analytic hierarchy process will be used to assess and describe the risk level of data cross-border operations. Then, the risk threshold is calculated, and the wavelet neural network is used to simulate the evaluation process. Ultimately, the prospect of cross-border data can provide references for the development and research of cross-border data in the future.KeywordsCross-border dataRisk assessmentWavelet theoryBP neural network