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Neural Control Based Research of Endogenous Security Model

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Artificial Intelligence and Security (ICAIS 2021)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12737))

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Abstract

With the development of information technology, the architecture of information system has become increasingly complex, and the performance of terminal equipment has become stronger. The existing centralized defense and passive defense methods will cause problems such as low service efficiency and insufficient defense capabilities in future networks. This paper proposes an endogenous security protection mechanism based on neural control of the human body. The main purpose of this paper is to learn from neural control mechanism, and build an autonomous active defense mechanism, so that the security elements and functional elements of the system can be highly integrated. This paper firstly mapped the human nerve control to the information system through the study of the human nerve control system. Then the nervous system-like control architecture was constructed, and a task-oriented execution architecture was rebuilt. In proposed system, security elements and functional elements are highly integrated into one model. The verification based on the prototype system construction framework shows that this endogenous security model based on neural control can maintain the security of the information system.

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Acknowledgments

This research was supported by Zhishan Youth Scholar Program Of SEU, Purple Mountain Laboratories for Network and Communication Security, National Science Foundation (No. 61601113).

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Correspondence to Xu Hu .

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Li, T., Hu, X., Hu, A. (2021). Neural Control Based Research of Endogenous Security Model. In: Sun, X., Zhang, X., Xia, Z., Bertino, E. (eds) Artificial Intelligence and Security. ICAIS 2021. Lecture Notes in Computer Science(), vol 12737. Springer, Cham. https://doi.org/10.1007/978-3-030-78612-0_20

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  • DOI: https://doi.org/10.1007/978-3-030-78612-0_20

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-78611-3

  • Online ISBN: 978-3-030-78612-0

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