Learning Is Change in Knowledge: Knowledge-Based Security for Dynamic Policies
In systems that handle confidential information, the security policy to enforce on information frequently changes: new users join the system, old users leave, and sensitivity of data changes over time. It is challenging, yet important, to specify what it means for such systems to be secure, and to gain assurance that a system is secure. The authors present a language-based model for specifying, reasoning about, and enforcing information security in systems that dynamically change the security policy. They specify security for such systems as a simple and intuitive extensional knowledge-based semantic condition: an attacker can only learn information in accordance with the current security policy.