| Open Access SQOUT
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Pattern Recognition Using Machine Learning
Utilize machine learning with neural networks trained on simulations to recognize patterns of specific attacks.
Literature
| [Mao2020] | Y. Mao, Y. Wang, W. Huang, H. Qin, D. Huang, and Y. Guo. "Hidden-Markov-modelbased calibration-attack recognition for continuous-variable quantum key distribution" In: Phys. Rev. A 101, 062320. (2020) 10.1103/PhysRevA.101.062320. |
| [Mao2020a] | Y. Mao, W. Huang, H. Zhong, Y. Wang, H. Qin, Y. Guo, and D. Huang. "Detecting quantum attacks: a machine learning based defense strategy for practical continuous-variable quantum key distribution" In: New J. Phys. 22, 083073. (2020) 10.1088/1367-2630/aba8d4. |
Technique → Countermeasures
List of techniques where this countermeasure can be applied.
Items: 2
| Description | Technique |
|---|---|
|
Use machine learning on pattern recognition. |
Manipulation of Vacuum-Noise Estimation |
|
Use machine learning with pattern recognition. |
Saturation Attack |