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

作　　者：康茁 刘维琪 齐锦 贺晨 Zhuo Kang;Wei-Qi Liu;Jin Qi;Chen He(School of Information Science and Technology,Northwest University,Xi'an 710127,China)

机构地区：[1]School of Information Science and Technology,Northwest University,Xi'an 710127,China

出　　处：《Chinese Physics B》2024年第5期255-262,共8页中国物理B（英文版）

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

摘　　要：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.

关 键 词：CVQKD generative adversarial network attack classification 

分 类 号：TN752[电子电信—电路与系统] O413[理学—理论物理] TN918.4[理学—物理]