Runtime enforcement seeks to provide a valid replacement to any misbehaving sequence of events of a running system so that the correct sequence complies with a user-defined security policy. However, depending on the capabilities of the enforcement mechanism, multiple possible replacement sequences may be available, and the current literature is silent on the question of how to choose the optimal one. In this paper, we propose a new model of enforcement monitors, that allows the comparison between multiple alternative corrective enforcement actions and the selection of the optimal one, with respect to an objective user-defined gradation, separate from the security policy. These concepts are implemented using the event stream processor BeepBeep and a use case is presented. Experimental evaluation shows that our proposed framework can dynamically select enforcement actions at runtime, without the need to manually define an enforcement monitor.
Abstract. The context itself has multiple meanings may vary according to the domain of application. This contextual flexibility was behind the emergence of so such huge number of context definitions. Nevertheless, all the proposed definitions do not provide solid ground for systems developers' expectations, especially in healthcare domain [1]. This issue prompted researchers to divide the context into a set of concepts that would facilitate organizing of contextual knowledge. The conventional taxonomies of context are always too complex, and we need to fight to make them useful in the intended application area. In this paper, we propose a new context classification which covers almost all the context aspects that we may need to develop a tele-monitoring system for chronic disease management.
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