Modeling security-relevant data semantics

The use of an extended data model which represents both integrity and secrecy aspects of data is demonstrated. This Semantic Data Model for Security (SDMS) provides a technique that assists domain experts, security officers, and database designers in first understanding their security requirements, and then translating them into a good database design. Identifying security requirements at this semantic level provides the basis for analyzing the security requirements and the database design for inference and signaling vulnerabilities. Another contribution is a comprehensive taxonomy of security-relevant data semantics that must be captured and understood to implement a multilevel secure automated information system.<
>