Secure Data Collection Method Based on Quantum Encryption Algorithm for Power IoT Gateway
In order to realize the secure and high-efficiency collection of electric power IoT gateway data, the secure collection method of electric power IoT gateway data based on quantum encryption algorithm is proposed. By analyzing the architecture of electric power IoT, the generation logic of electric p...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | Chinese |
| Published: |
Post&Telecom Press Co.,LTD
2025-06-01
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| Series: | 天地一体化信息网络 |
| Subjects: | |
| Online Access: | http://www.j-sigin.com.cn/zh/article/doi/10.11959/j.issn.1000-0801.2025022/ |
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| Summary: | In order to realize the secure and high-efficiency collection of electric power IoT gateway data, the secure collection method of electric power IoT gateway data based on quantum encryption algorithm is proposed. By analyzing the architecture of electric power IoT, the generation logic of electric power IoT gateway data is clarified. Based on the specific architectural level, the attribute feature vector of the gateway data is extracted. Based on the quantum encryption algorithm, the original quantum key is obtained by selecting the two-dimensional Henon chaotic mapping method through the feature vector. The original keys in different quantum states are encoded and processed to output the bit sequences with the information of security key. Based on the output security key, encryption, decryption, user authentication operation, synchronized secondary encryption and data acquisition instruction execution are carried out to realize the secure data acquisition of electric power IoT gateway data in the process of data transmission and communication. The experimental results show that the designed method can effectively handle gateway data in various formats such as JSON, XML, Protobuf, etc. The overall data encryption time is short, not exceeding 180 ms. The average packet loss rate of the data fluctuates from 0.07 to 0.14, and the highest average throughput value reaches 8.2 × 10<sup>3</sup>, which provides high data collection security and collection efficiency. |
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| ISSN: | 2096-8930 |