Abstract
Organization assets and resources are administered to be accessed by some members and not by others. The high sensitivity of assets (e.g. patients’ health record and sensitive medical devices) in medical centers, requires the managers to pay special attention to deploy reliable authorization models. A reliable authorization model must be able to resolve the contingent conflicts that can occur due to different authorization assignments to subjects (e.g. technicians). Resolving conflicts is quite a challenge due to the existence of sophisticated inheritance hierarchies that might cause an exponential number of conflicts (in terms of the number of subjects in the organization hierarchy) and the diversity of ways to combine resolution policies. The need to an approach that can handle as much contingent conflicts and resolution policies as possible and work in an appropriate time emerges here. An existing work has presented an exponential algorithm for resolving all conflicts in accordance to all existing policies. This paper develops a dynamic programming (DP) algorithm with a polynomial time complexity for the same conditions. The two approaches were compared by doing three different experiments with both algorithms and comparing the results. The experiments show that the average time decreased to 1/10 on small SDAGs with maximum number of edges. The improvement for large sparse SDAGs is more significant (3/1000). The average time of determining the authorization of a subject over 500 objects is just 52.56 s.
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Acknowledgment
We thank Dr. Amirhossein Chinaei for introducing the topic of the research and his valuable contribution on the review of the work in its early stages. We also thank Colgate University Faculty Research Council for financially supporting the work.
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Samadian, H., Tuiyot, D., Valera, J. (2020). Dynamic Programming Approach in Conflict Resolution Algorithm of Access Control Module in Medical Information Systems. In: Arai, K., Kapoor, S., Bhatia, R. (eds) Advances in Information and Communication. FICC 2020. Advances in Intelligent Systems and Computing, vol 1129. Springer, Cham. https://doi.org/10.1007/978-3-030-39445-5_49
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