Implementing Database Access Control Policy from Unconstrained Natural Language Text
North Carolina State University, USA
Track: Doctoral Symposium
Although software can and does implement access control at the application layer, failure to enforce data access at the data layer often allows uncontrolled data access when individuals bypass application controls. The goal of this research is to improve security and compliance by ensuring access controls rules explicitly and implicitly defined within unconstrained natural language texts are appropriately enforced within a systems relational database. Access control implemented in both the application and data layers strongly supports a defense in depth strategy. We propose a tool-based process to 1) parse existing, unaltered natural language documents; 2) classify whether or not a statement implies access control and whether or not the statement implies database design; and, as appropriate, 3) extract policy elements; 4) extract database design; 5) map data objects found in the text to a database schema; and 6) automatically generate the necessary SQL commands to enable the database to enforce access control. Our initial studies of the first three steps indicate that we can effectively identify access control sentences and extract the relevant policy elements.