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Issue title: Artificial Intelligence and Advanced Manufacturing (AIAM 2020)
Guest editors: Shengzong Zhou
Article type: Research Article
Authors: Zhu, Wenye; * | Tan, Chengxiang | Xu, Qian | Xiao, Ya
Affiliations: Department of Computer Science and Technology, Tongji University, Shanghai, China
Correspondence: [*] Corresponding author. Wenye Zhu, Department of Computer Science and Technology, Tongji University, Shanghai 200092, China. E-mail: [email protected].
Abstract: The cross-trust domain environment in which heterogeneous identity alliances are located often does not have a completely trusted centralized trust root, and different trust domains and entities also have specific security requirements. In view of the above problems, we believe that trust measurement of cross-domain identities based on risk assessment is an effective method to achieve decentralized proof of user identities in heterogeneous cyberspace. There are various risk assessment models. We choose the more mature attack graph theory in the existing research to apply to the new field of cross-trust domain management of heterogeneous identities. We propose an attribute attack graph evaluation model to evaluate cross-domain identities through risk measurement of attributes. In addition, heterogeneous identity alliances also have architectural risks, especially the risk of decentralized underlying structures. In response to this problem, we identify the risk of the identity alliance infrastructure, and combine the risk assessment and presentation system design to verify the principle.
Keywords: Heterogeneous identity alliance, attribute attack graph, proof of identity, cyber security assessment, trust management
DOI: 10.3233/JIFS-189729
Journal: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 3, pp. 4691-4704, 2021
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