Secure Continuous-Variable Quantum Key Distribution with Machine Learning

Photonics

Ling Zhang¹  Susu Liu²  Duan Huang² 

[1] School of Automation, Central South University, Changsha 410083, China;School of Computer Science and Engineering, Central South University, Changsha 410083, China;

关键词: CVQKD;    machine learning;    attack and defense;   

DOI  :  10.3390/photonics8110511

来源: DOAJ

【 摘 要 】

Quantum key distribution (QKD) offers information-theoretical security, while real systems are thought not to promise practical security effectively. In the practical continuous-variable (CV) QKD system, the deviations between realistic devices and idealized models might introduce vulnerabilities for eavesdroppers and stressors for two parties. However, the common quantum hacking strategies and countermeasures inevitably increase the complexity of practical CV systems. Machine-learning techniques are utilized to explore how to perceive practical imperfections. Here, we review recent works on secure CVQKD systems with machine learning, where the methods for detections and attacks were studied.

【 授权许可】

Unknown