Research and implementation of an authentication system fusing physical layer and behavioral fingerprinting for power systems
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| Publicado en: | EURASIP Journal on Advances in Signal Processing vol. 2025, no. 1 (Dec 2025), p. 47 |
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| Autor principal: | |
| Otros Autores: | , , , , , |
| Publicado: |
Springer Nature B.V.
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| Acceso en línea: | Citation/Abstract Full Text Full Text - PDF |
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| 045 | 2 | |b d20251201 |b d20251231 | |
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| 100 | 1 | |a Chen, Mu |u China Electric Power Research Institute Co., Ltd, Nanjing, China (ISNI:0000 0004 5928 1249); State Grid Laboratory of Power Cyber-Security Protection and Monitoring Technology, Nanjing, China; Xiamen University, Xiamen, China (GRID:grid.12955.3a) (ISNI:0000 0001 2264 7233) | |
| 245 | 1 | |a Research and implementation of an authentication system fusing physical layer and behavioral fingerprinting for power systems | |
| 260 | |b Springer Nature B.V. |c Dec 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a With the rapid growth of resource integration in modern power systems, these resources are diverse, large-scale, and situated in complex and open physical environments, making them relatively vulnerable to cyber-attacks due to weaker security measures. To address this challenge, this paper proposes an identity authentication architecture system that integrates software and hardware. In the software fingerprint section, we extract packet characteristics and statistical features through network probing, and combine them with time difference sequence features obtained from side-channel monitoring to generate the software fingerprint of the power smart terminal by direct concatenation. This method incorporates various characteristic informations, enhancing the recognition accuracy of the fingerprint features. In the hardware fingerprint section, we generate hardware fingerprints by extracting the preamble signal and performing statistical feature analysis. Finally, using an ensemble learning method, we integrate the software and hardware fingerprints to generate device fingerprint features. This approach effectively addresses the security authentication issue of power equipment based on High-Level Power Line Communication (HPLC), achieving a recognition rate of over 95% under most machine learning classification methods. | |
| 653 | |a Forgery | ||
| 653 | |a Software | ||
| 653 | |a Data integrity | ||
| 653 | |a Security | ||
| 653 | |a Fingerprinting | ||
| 653 | |a Hardware | ||
| 653 | |a Signal processing | ||
| 653 | |a Process controls | ||
| 653 | |a Data processing | ||
| 653 | |a Power lines | ||
| 653 | |a Data collection | ||
| 653 | |a Transmitters | ||
| 653 | |a Data encryption | ||
| 653 | |a Fingerprints | ||
| 653 | |a Algorithms | ||
| 653 | |a Machine learning | ||
| 653 | |a Authentication | ||
| 653 | |a Ensemble learning | ||
| 653 | |a Efficiency | ||
| 700 | 1 | |a Li, Nige |u China Electric Power Research Institute Co., Ltd, Nanjing, China (GRID:grid.12955.3a) (ISNI:0000 0004 5928 1249); State Grid Laboratory of Power Cyber-Security Protection and Monitoring Technology, Nanjing, China (GRID:grid.12955.3a) | |
| 700 | 1 | |a Li, Yong |u China Electric Power Research Institute Co., Ltd, Nanjing, China (GRID:grid.12955.3a) (ISNI:0000 0004 5928 1249); State Grid Laboratory of Power Cyber-Security Protection and Monitoring Technology, Nanjing, China (GRID:grid.12955.3a) | |
| 700 | 1 | |a Zhang, Bo |u China Electric Power Research Institute Co., Ltd, Nanjing, China (GRID:grid.12955.3a) (ISNI:0000 0004 5928 1249); State Grid Laboratory of Power Cyber-Security Protection and Monitoring Technology, Nanjing, China (GRID:grid.12955.3a); Shanghai Jiao Tong University, Shanghai, China (GRID:grid.16821.3c) (ISNI:0000 0004 0368 8293) | |
| 700 | 1 | |a Xiao, Yongcai |u State Grid Jiangxi Electric Power Research Institute, NanChang, China (GRID:grid.433158.8) (ISNI:0000 0000 8891 7315) | |
| 700 | 1 | |a Wang, Tengyan |u China Electric Power Research Institute Co., Ltd, Nanjing, China (GRID:grid.433158.8) (ISNI:0000 0004 5928 1249); State Grid Laboratory of Power Cyber-Security Protection and Monitoring Technology, Nanjing, China (GRID:grid.433158.8) | |
| 700 | 1 | |a Lu, Ziang |u China Electric Power Research Institute Co., Ltd, Nanjing, China (GRID:grid.433158.8) (ISNI:0000 0004 5928 1249); State Grid Laboratory of Power Cyber-Security Protection and Monitoring Technology, Nanjing, China (GRID:grid.433158.8) | |
| 773 | 0 | |t EURASIP Journal on Advances in Signal Processing |g vol. 2025, no. 1 (Dec 2025), p. 47 | |
| 786 | 0 | |d ProQuest |t Advanced Technologies & Aerospace Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3255933270/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text |u https://www.proquest.com/docview/3255933270/fulltext/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3255933270/fulltextPDF/embedded/6A8EOT78XXH2IG52?source=fedsrch |