Advances in Anti-Surveying-and-Mapping Theory and Technologies for Data Infrastructure
China is deepening its digital transformation and promoting a data-driven action plan, proposing new requirements for the construction of data infrastructure. Like conventional information infrastructure types, data infrastructure needs to possess an anti-surveying-and-mapping capability to avoid be...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
《中国工程科学》杂志社
2025-02-01
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| Series: | 中国工程科学 |
| Subjects: | |
| Online Access: | https://www.engineering.org.cn/sscae/EN/PDF/10.15302/J-SSCAE-2025.09.027 |
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| Summary: | China is deepening its digital transformation and promoting a data-driven action plan, proposing new requirements for the construction of data infrastructure. Like conventional information infrastructure types, data infrastructure needs to possess an anti-surveying-and-mapping capability to avoid being detected in one-way and transparent manners. The anti-surveying-and-mapping capability of data infrastructure has become a fundamental requirement for data space security, directly related to the information security of a country, society, and individuals. This study outlines the basic concepts of data infrastructure surveying-and-mapping and anti-surveying-and-mapping, analyzes the development status, major characteristics, and key problems of mainstream anti-surveying-and-mapping technologies, and proposes the theory, methods, and key technologies of anti-surveying-and-mapping with endogenous security, to solve the key problem of inherent measurability of data assets under the existing network architecture. To this end, the following suggestions are proposed: strengthening research on the basic theories and key technologies regarding data space anti-surveying-and-mapping; taking anti-surveying-and-mapping capability as the basic requirement of national data infrastructure construction; and increasing support for key technology research, industry incubation, multidisciplinary integration, and industry-university-research collaboration. |
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| ISSN: | 1009-1742 |