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Mobile Internet Access Control Strategy Based on Trust Perception

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Artificial Intelligence and Security (ICAIS 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13340))

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Abstract

In recent years, the rapid development of mobile Internet services has greatly increased the complexity of network interaction. In the mobile Internet scenario, there are higher requirements for the dynamic and fine-grained access control. However, the existing access control strategy is mainly based on static access control mechanism, which cannot meet its needs. For this reason, this paper proposes a mobile internet access control strategy based on trust perception, which improves the outstanding problems of traditional access control methods such as not supporting dynamic authorization and coarse-grained. This strategy combines the advantages of both the role-based access control (RBAC) model and the attribute-based access control (ABAC) model. And introduce comprehensive trust evaluation to quantify user trust, and realize dynamic authorization and fine-grained access control based on trust perception. User trust consists of two parts: attribute trust and historical trust. Attribute trust is derived based on the user's attributes, and historical trust is calculated based on the user's historical access behavior. Finally, this article simulates the two most common attack methods, bleaching attack and betrayal attack. Comparative experiments show that the method proposed in this paper has better ability to resist bleaching attacks and betrayal attacks.

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Funding

This work is supported by the science and technology project of State Grid Corporation of China Funding Item: “Research on Dynamic Access Authentication and Trust Evaluation Technology of Power Mobile Internet Services Based on Zero Trust” (Grand No. 5700-202158183A-0-0-00).

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Correspondence to Lu Chen .

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Chen, L. et al. (2022). Mobile Internet Access Control Strategy Based on Trust Perception. In: Sun, X., Zhang, X., Xia, Z., Bertino, E. (eds) Artificial Intelligence and Security. ICAIS 2022. Lecture Notes in Computer Science, vol 13340. Springer, Cham. https://doi.org/10.1007/978-3-031-06791-4_47

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  • DOI: https://doi.org/10.1007/978-3-031-06791-4_47

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-06790-7

  • Online ISBN: 978-3-031-06791-4

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