Abstract
In order to meet the higher security requirements of authentication technology under the current mobile Internet background, continuous identity authentication technology based on single authentication improvement came into being. At present, continuous authentication technology has problems such as low security, low efficiency, and lack of a scientific punishment mechanism. How to efficiently, safely and comprehensively evaluate the legal and illegal requests of the terminal is a huge challenge for continuous authentication. The multi-device continuous authentication mechanism based on homomorphic encryption and SVM algorithm can satisfy the server in a sufficiently secure environment to enable the terminal request to be continuously authenticated. Moreover, based on the existing research, this paper designs a new penalty protocol and applies it to the continuous authentication mechanism. For this purpose, an illegal request processing model is constructed, and the penalty protocol designed to cope with the illegal request Further processing solves the problem that the existing continuous authentication mechanism is insufficient to handle illegal requests and is not humane enough. Finally, the experimental results of SVM and convolutional network on a single device and multiple devices are compared from three dimensions. The comparison of the experimental results verifies the effectiveness of the proposed model and protocol.
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Acknowledgement
This work is supported by the State Grid Sichuan Company Science and Technology Project: “Research and Application of Key Technologies of Network Security Protection System Based on Zero Trust Model” (No. SGSCCD00XTJS2101279).
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The authors declare that they have no conflicts of interest to report regarding the present study.
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Gan, W. et al. (2022). Multi-device Continuous Authentication Mechanism Based on Homomorphic Encryption and SVM Algorithm. 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_49
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