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• W2956007097 abstract "Efficient identity management system has become one of the fundamental requirements for ensuring safe, secure and transparent use of cloud services. In such a borderless environment, entities belonging to different network domains need to cooperate dynamically with each other by exchanging and sharing a significant amount of personal information in a scalable, effective and seamless manner. The traditional approach to address this challenge has been identity federation, aiming to simplify the user experience by aggregating distributed rights and permissions. However, the current federated identity management solutions are missing mechanisms to achieve agile and dynamic trust management, which remains one of the biggest obstacles to their wide adoption in cloud computing. In this paper, we aim to address this issue by introducing a novel dynamic trust model for Federated Identity Management. The proposed model relies on fuzzy cognitive maps for modeling and evaluating trust relationships between the involved entities in federated identity management systems. This trust mechanism facilitates the creation of trust relationships between prior unknown entities in a secure and dynamic way and makes Federated Identity Management systems more scalable and flexible to deploy and maintain in cloud computing environments. In addition, we propose a set of trust features for Federated Identity Management, which serves as a basis for modeling and quantifying the trust level of unknown entities. The effectiveness of the proposed trust model is proven through performance analysis and experimental results." @default.
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• W2956007097 date "2019-09-01" @default.
• W2956007097 modified "2023-10-11" @default.
• W2956007097 title "FCMDT: A novel fuzzy cognitive maps dynamic trust model for cloud federated identity management" @default.
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• W2956007097 doi "https://doi.org/10.1016/j.cose.2019.06.011" @default.
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