Data security for object-oriented programming systems based on inference engines

Protecting data stored in a computer is a difficult task, particularly in a society which has become increasingly dependent on computer systems. This paper focuses on a new model which has been proposed for data security and explores the extension of this model to object-oriented programming systems. The model uses both a trusted filter and an inference engine to provide security in a dynamically changing environment. The filter component protects against Trojan Horse release and direct user release, while the inference engine used rules which specify security constraints to decide if access to requested data should be allowed. The rule base is constantly updated any time information is released, thus protecting against user inference dynamically. The model is extended to apply to object-oriented programming systems.