General multi-attack detection for continuous-variable quantum key distribution with local local oscillator

doi:10.1088/1674-1056/ad2bf2

Abstract Continuous-variable quantum key distribution with a local local oscillator (LLO CVQKD) has been extensively researched due to its simplicity and security. For practical security of an LLO CVQKD system, there are two main attack modes referred to as reference pulse attack and polarization attack presently. However, there is currently no general defense strategy against such attacks, and the security of the system needs further investigation. Here, we employ a deep learning framework called generative adversarial networks (GANs) to detect both attacks. We first analyze the data in different cases, derive a feature vector as input to a GAN model, and then show the training and testing process of the GAN model for attack classification. The proposed model has two parts, a discriminator and a generator, both of which employ a convolutional neural network (CNN) to improve accuracy. Simulation results show that the proposed scheme can detect and classify attacks without reducing the secret key rate and the maximum transmission distance. It only establishes a detection model by monitoring features of the pulse without adding additional devices.

Keywords: CVQKD generative adversarial network attack classification

Received: 13 December 2023
Revised: 01 February 2024
Accepted manuscript online: 22 February 2024

PACS:	03.67.-a	(Quantum information)
	03.67.Ac	(Quantum algorithms, protocols, and simulations)
	03.67.Lx	(Quantum computation architectures and implementations)
	07.05.Pj	(Image processing)

Fund: Project supported by the National Natural Science Foundation of China (Grant No. 62001383).

Corresponding Authors: Wei-Qi Liu,E-mail:vickylwq1991@nwu.edu.cn
E-mail: vickylwq1991@nwu.edu.cn

Cite this article:

Zhuo Kang(康茁), Wei-Qi Liu(刘维琪), Jin Qi(齐锦), and Chen He(贺晨) General multi-attack detection for continuous-variable quantum key distribution with local local oscillator 2024 Chin. Phys. B 33 050308

[1] Grosshans F and Grangier P 2002 Phys. Rev. Lett. 88 057902
[2] Gisin N, Ribordy GG, Tittel W and Zbinden H 2002 Rev. Mod. Phys. 74 145
[3] Weedbrook C, Pirandola S, García-Patrón R, Cerf N J, Ralph T C, Shapiro J H and Lloyd S 2012 Rev. Mod. Phys. 84 621
[4] Renner R and Cirac J I 2009 Phys. Rev. Lett. 102 110504
[5] Furrer F, Franz T, Berta M, Leverrier A, Scholz V B, Tomamichel M and Werner R F 2012 Phys. Rev. Lett. 109 100502
[6] Leverrier A 2017 Phys. Rev. Lett. 118 200501
[7] Zhang Y C, Chen Z Y, Pirandola S, Wang X Y, Zhou C, Chu B J, Zhao Y J, Xu B J, Yu S and Guo H 2020 Phys. Rev. Lett. 125 010502
[8] Pi Y D, Wang H, Pan Y, Shao Y, Li Y, Yang J, Zhang Y C, Huang W and Xu B J 2023 Opt. Lett. 48 1766
[9] Tian Y, Zhang Y, Liu S H, Wang P, Lu Z G, Wang X Y and Li Y M 2023 Opt. Lett. 48 2953
[10] Marie A and Alleaume R 2017 Phys. Rev. A 95 012316
[11] Ma X C, Sun S H, Jiang M S and Liang L M 2013 Phys. Rev. A 88 022339
[12] Jouguet P, Kunz-Jacques S and Diamanti E 2013 Phys. Rev. A 87 062313
[13] Qi B, Lougovski P, Pooser R, Grice W and Bobrek M 2015 Phys. Rev. X 5 041009
[14] Soh D B S, Brif C, Coles P J, Luetkenhaus N, Camacho R M, Urayama J J and Sarovar M 2015 Phys. Rev. X 5 041010
[15] Huang D, Huang P, Lin D, Wang C and Zeng G H 2015 Opt. Lett. 40 3695
[16] Wang T, Huang P, Zhou Y M, Liu W Q, Ma H X, Wang S Y and Zeng G H 2018 Opt. Express 26 2794
[17] Wang T, Huang P, Zhou Y M, Liu W Q and Zeng G H 2018 Phys. Rev. A 97 012310
[18] Xu F H, Ma X F, Zhang Q, Lo H K and Pan J W 2020 Rev. Mod. Phys. 92 025002
[19] Guo H, Li Z Y, Yu S and Zhang Y C 2021 Fundam. Res. 1 96
[20] Wang H, Pi Y D, Huang W, Li Y, Shao Y, Yang J, Liu J L, Zhang C L, Zhang Y C and Xu B J 2020 Opt. Express 28 32882
[21] Ren S J, Kumar R, Wonfor A, Tang X K, Penty R and White I 2019 J. Opt. Soc. Am. B 36 B7
[22] Shao Y, Wang H, Pi Y D, Huang W, Li Y, Liu J L, Yang J, Zhang Y C and Xu B J 2021 Phys. Rev. A 104 032608
[23] Shao Y, Pan Y, Wang H, Pi Y D, Li Y, Ma L, Zhang Y C, Huang W and Xu B J 2022 Entropy 24 992
[24] Shao Y, Li Y, Wang H, Pan Y, Pi Y D, Zhang Y C, Huang W and Xu B J 2022 Phys. Rev. A 105 032601
[25] Alaghbari K A, Rumyantsev K, Eltaif T, Elmabrok O and Lim H S 2021 IEEE Photon. J. 13 7600107
[26] Huang B, Huang Y M and Peng Z M 2019 Opt. Express 27 20621
[27] Huang D, Liu S S and Zhang L 2021 Photonics 8 511
[28] Huang W T, Mao Y Y, Xie C and Huang D 2019 Phys. Rev. A 100 012316
[29] Mao Y Y, Wang Y J, Huang W T, Qin H, Huang D and Guo Y 2020 Phys. Rev. A 101 062320
[30] Luo H S, Zhang L, Qin H, Sun S H, Huang P, Wang Y J, Wu Z J, Guo Y and Huang D 2022 Phys. Rev. A 105 042411
[31] Mao Y Y, Huang W T, Zhong H, Wang Y J, Qin H, Guo Y and Huang D 2020 New J. Phys. 22 083073
[32] Du H W and Huang D 2022 Photonics 9 177
[33] Liu W Q, Huang P, Peng J Y, Fan J P and Zeng G H 2018 Phys. Rev. A 97 022316
[34] He Z, Wang Y J and Huang D 2020 J. Opt. Soc. Am. B 37 1689
[35] Li S M, Yin P Z, Zhou Z H, Tang J H, Huang D and Zhang L 2023 Entropy 25 499
[36] Goodfellow I, Pouget-Abadie J, Mirza M, Xu B, Warde-Farley D, Ozair S, Courville A and Bengio Y 2020 Commun. ACM 63 139
[37] Odena A, Olah C and Shlens J 2017 Proceedings of Machine Learning Research 70 2642
[38] Ravanbakhsh M, Nabi M, Sangineto E, Marcenaro L, Regazzoni C and Sebe N 2017 IEEE International Conference on Image Processing (ICIP), Beijing, China, 2017, pp. 1577-1581
[39] Jolliffe I T and Cadima J 2016 Philos. Trans. R. Soc. A 374 20150202
[40] Cook N R 2007 Circulation 115 928
[41] Liao Q, Xiao G, Zhong H and Guo Y 2020 New J. Phys. 22 083086
[42] Shelhamer E, Long J and Darrell T 2017 IEEE Trans. Pattern Anal. 39 640

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General multi-attack detection for continuous-variable quantum key distribution with local local oscillator

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