Research on Data Security Protection System of Monitoring and Acquisition System Based on Block Chain Technology
The monitoring collection system is a system that uses computer, control and other technologies to realize the data storage, collection and monitoring of the field environment. It is widely used in data collection and monitoring in various fields. It often collects data generated by various types of...
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Published in | Advances in Artificial Intelligence and Security pp. 502 - 513 |
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Main Authors | , , , |
Format | Book Chapter |
Language | English |
Published |
Cham
Springer International Publishing
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Series | Communications in Computer and Information Science |
Subjects | |
Online Access | Get full text |
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Summary: | The monitoring collection system is a system that uses computer, control and other technologies to realize the data storage, collection and monitoring of the field environment. It is widely used in data collection and monitoring in various fields. It often collects data generated by various types of equipment during operation through various sensors and actuators, and these collected data are often the key to analyzing system failures and discovering that equipment is under network attack. In the current environment, attacks occur frequently, and how to protect and utilize these data is very important. Therefore, data security protection system of monitoring and acquisition system Based on blockchain is proposed. Its purpose is to improve data security and better use of data. By combining the blockchain technology, the collected data is stored on the blockchain, and the integrity check mechanism is used to ensure the integrity of the collected data and prevent the data from being tampered with. The association rule base is formed by establishing association rules, and the rule base is used to analyze data, detect data anomalies and feed back the analysis results to the administrator. The data security and system security of the monitoring acquisition system is improved, and the burden of manpower analysis of data is reduced. |
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ISBN: | 303078620X 9783030786205 |
ISSN: | 1865-0929 1865-0937 |
DOI: | 10.1007/978-3-030-78621-2_42 |