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Cloud Computing Information System Security Monitoring Under Artificial Intelligence Technology

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Proceedings of the 4th International Conference on Big Data Analytics for Cyber-Physical System in Smart City - Volume 1 (BDCPS 2022)

Abstract

Cloud computing (CC) represents the trend of IT field towards the road of intensification, scale and specialization, and is a profound change that is happening in the IT field. It greatly improves the efficiency of using various resources, but also brings great impact and challenges to the security and privacy protection of users’ information assets. In this paper, we take a dam cloud computing information system as an example, use Revit as a platform, combine Visual Studio and C# language, secondary development of Revit, and establish a dam safety monitoring BIM IS. The monitoring data management module completes the interaction between Revit and database through Visual Studio and C# language, and adopts two ways of monitoring instrument 3D model and command button to realize the association between each monitoring item and monitoring data; the monitoring data analysis module embeds the mathematical model established by the research into the system to realize the modeling prediction of dam safety monitoring data. The research results show that the development of the dam cloud platform safety monitoring BIM IS with the functions of dam structure management, monitoring instrument management, monitoring data management and monitoring data analysis is of positive significance to improve the efficiency of dam safety monitoring and promote the development of dam safety monitoring technology.

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Correspondence to Shen Qin .

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Lao, C., Qin, S. (2023). Cloud Computing Information System Security Monitoring Under Artificial Intelligence Technology. In: Atiquzzaman, M., Yen, N., Xu, Z. (eds) Proceedings of the 4th International Conference on Big Data Analytics for Cyber-Physical System in Smart City - Volume 1. BDCPS 2022. Lecture Notes on Data Engineering and Communications Technologies, vol 167. Springer, Singapore. https://doi.org/10.1007/978-981-99-0880-6_81

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