量子电子学报2025，Vol.42Issue(6)：818-828,11.DOI:10.3969/j.issn.1007-5461.2025.06.009
基于KNN的连续变量量子密钥分发实际攻击检测
Practical attacks detection of continuous-variable quantum key distribution based on KNN
摘要
Abstract
Continuous-variable quantum key distribution(CVQKD)has theoretical unconditional security,which is based on the assumption that the physical devices at the sender and receiver operate perfectly and are secure and reliable.However,in practical CVQKD systems,the eavesdropper can launch attacks from three aspects—source,channel,and detection end—by exploiting the physical flaws inherent in actual devices,thereby compromising the practical security of the system.Although corresponding defense strategies have been developed for some practical quantum attacks,each strategy can only defend against specific attack types,lacking a universal defense approach effective against most attacks.By combining machine learning techniques with attacks detection in the CVQKD,we propose a practical attacks detection scheme in this work based on the K-nearest neighbors(KNN)algorithm.This scheme extracts features from the optical pulses of the CVQKD system,trains a KNN prediction model through learning,and ultimately deploys the model at the receiver end of the CVQKD system to detect practical quantum attacks.Simulation results demonstrate that the proposed attack detection scheme can effectively identify various typical quantum attacks targeting CVQKD,with both precision and recall rates exceeding 98%.关键词
量子信息/连续变量量子密钥分发/实际安全性/攻击检测/机器学习Key words
quantum information/continuous-variable quantum key distribution/practical security/attacks detection/machine learning分类
电子信息工程引用本文复制引用
刘潺,黄磊,王铮,朱凌瑾..基于KNN的连续变量量子密钥分发实际攻击检测[J].量子电子学报,2025,42(6):818-828,11.基金项目
湖南省重点研发计划(2023GK2021,2023GK2054) （2023GK2021,2023GK2054）
