Configurable Rule Engine for Industrial Data Flow Scenarios

Abstract

With the integration of new generation information technology and industry, the value of industrial data has been highly valued. Meanwhile, enterprises are also facing various data security threats and urgently need to establish a trusted and controllable industrial data circulation platform and ecosystem, to eliminate enterprise concerns, unleash the vitality of data element sharing and circulation. This paper uses principal component analysis to classify, filter, transform or process the dataset, supporting the configuration of warning rules. Subsequently, based on a configurable rule engine, security policy verification and abnormal behavior warning are executed to achieve real-time supervision and tracking of the entire data circulation process, timely discover and warn of risk behaviors, avoid the risk of data leakage and protect data circulation security.