Big Data Security Evaluation by Bidirectional Analysis of Access Control Policy

Big Data, the advanced technology that harnesses the value of huge volumes of varied data through real-time processing, is presented today in almost all areas of the smart industry. Big Data collection, processing, and storing use heterogeneous instruments and various types of data transforming operations. Big Data sustainability and security are tightly linked to smart industry security. Different data fragments migrating through a smart system contain semantically related information, and thus it is hard to trace data misuse along the data route. Such specifics are not concerned when evaluating cybersecurity and resiliency if applying conventional security evaluation techniques based on static, ontological, neural networking, risk-oriented or other types of analysis. This work proposes a novel technique for Big Data security evaluation that utilizes a data processing graph and a bidirectional analysis of data access. It performs the compliance of real access abilities with the given access control policy. A security evaluation framework prototype has been developed to automate our method and demonstrate its opportunities.