Usage control model (UCON) is based on the idea that attributes required for decision-making can be changed over a period of usage. Since it is not always possible to get a fresh and trustworthy value of attributes, a decision has to be done with some uncertainties in mind. Moreover, modern systems become more distributed and dynamic and this evolution aggravates the problem. Such trend demands for the solutions capable of working with imprecise values. Our study concerns analysis of risks to make access decision of usage control more credible. We consider the risks associated with imperfect mechanisms collecting information about an authorization context. To cope with these risks we introduce our approach based on Markov chains, which aims to help in making a decision to allow further access or to deny it. The proposed approach could be useful for designers of the policy enforcement engines based on the UCON model.

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Abstract. Dynamic and evolving systems might require flexible access control mechanisms, in order to make sure that the unavailability of some users does not prevent the system to be functional, in particular for emergency-prone environments, such as healthcare, natural disaster response teams, or military systems. The auto-delegation mechanism, which combines the strengths of delegation systems and "break-theglass" policies, was recently introduced to handle such situations, by stating that the most qualified available user for a resource can access this resource. In this work we extend this mechanism by considering availability as a quantitative measure, such that each user is associated with a probability of availability. The decision to allow or deny an access is based on the utility of each outcome and on a risk strategy. We describe a generic framework allowing a system designer to define these different concepts. We also illustrate our framework with two specific use cases inspired from healthcare systems and resource management systems.

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Security metrics are the tools for providing correct and upto-date information about a state of security. This information is essential for managing security efficiently. Although a number of security metrics were proposed we still need reliable ways for assessment of security. First of all, we do not have a widely-accepted and unambiguous definition which defines what it means that one system is more secure than another one. Without this knowledge we cannot show that a metric really measures security. Second, there is no a universal formal model for all metrics which can be used for rigourous analysis. In this paper we investigate how we can define "more secure" relation and propose our basic formal model for a description and analysis of security metrics.