Ontology Evolution in the Context of Model-Based Secure Software Engineering

Ontologies as a means to formally specify the knowledge of a domain of interest have made their way into information and communication technology. Most often, such knowledge is subject to continuous change, which demands for consistent evolution of ontologies and dependent artifacts. In this paper, we study ontology evolution in the context of a model-based approach to engineering of secure software, where ontologies are used to formalize the security context knowledge which is needed to come up with software systems which can be considered secure. In this application scenario, techniques for detecting ontology changes and determining their semantic impact are faced with a couple of challenging requirements which are not met by existing solutions. To overcome these shortcomings, we adapt a state-based approach to model differencing to OWL ontologies. Our solution is capable of detecting semantic editing patterns which may be customly defined using graph transformation rules, but it does not depend on information about editing processes such as persistently managed change logs. We showcase how to leverage semantic editing patterns for the sake of system model co-evolution in response to changing security context knowledge, and demonstrate the feasibility of the approach using a realistic medical information system.