基于长短期记忆网络的授时欺骗检测方法  

The time spoofing detection method based on Long Short-Term Memory network

作　　者：盛孟刚[1] 盛思缘 邓敏[1] 王礼亮 姚志强[1] SHENG Menggang;SHENG Siyuan;DENG Min;WANG Liliang;YAO Zhiqiang(School of Automation and Electronic Information,Xiangtan University,Xiangtan 411105,China;Liaoning Tianheng Zhitong Defense Technology Co.,Ltd.,ShenYang 110034,China)

机构地区：[1]湘潭大学自动化与电子信息学院智能可信导航与定位湖南省重点实验室,湖南湘潭411105 [2]辽宁天衡智通防务科技有限公司,沈阳110034

出　　处：《全球定位系统》2024年第4期86-91,共6页Gnss World of China

基　　金：国家重点研发计划(2020YFA0713502);湖南创新型省份建设专项经费资助(2023GK1040)。

摘　　要：时空信息安全是国家关键基础设施安全的基础,时间系统被阻断或受到干扰会对国家经济带来巨大损失,甚至对国防安全造成重大威胁.现有授时欺骗检测方法主要对接收机时钟模型变化特点建立模型,对欺骗进行检测.由于攻击方式的不确定性和建立的接收机时钟模型计算拟合过程中自身存在的系统误差,时钟模型参数准确拟合难度较大.环境适应能力较低.基于此,本文提出一种基于长短期记忆网络(long short-term memory,LSTM)的授时欺骗检测方法.该方法无需考虑授时欺骗的攻击方式,泛化能力强.根据授时欺骗前后接收机钟差变化的特点,利用LSTM优异的时间序列预测能力对接收机钟差变化趋势进行准确跟踪,实现对授时欺骗干扰的有效检测.最后使用TEXBAT(texas spoofing test battery)授时欺骗场景数据进行实验与分析,将LSTM与多层感知机(multilayer perceptron,MLP)进行实验对比.结果表明:LSTM授时欺骗检测的性能优于MLP.Temporal and spatial information security is fundamental to the safety of national critical infrastructure.Disruption or interference with the time system can cause significant economic losses to the nation,and even pose a substantial threat to defense security.Existing timing deception detection methods primarily establish models based on the characteristics of changes in the receiver’s clock model to detect deception.However,due to the uncertainty of attack methods and the system errors inherent in the established receiver clock model calculation and fitting process,accurate fitting of the clock model parameters is difficult,and the environmental adaptability is low.To address this,this paper proposes a timing deception detection method based on the Long Short-Term Memory(LSTM)network.This method does not require consideration of the attack methods of timing deception,and has strong generalization capabilities.By utilizing the excellent time series prediction ability of LSTM,the method accurately tracks the trend of changes in receiver clock differences before and after timing deception based on the characteristics of these changes,achieving effective detection of timing deception interference.Finally,experiments and analyses are conducted using TEXBAT(Texas spoofing test battery)timing deception scenario data,and a comparison is made between LSTM and Multilayer Perceptron(MLP)networks.The results indicate that the performance of LSTM timing deception detection is superior to that of MLP.

关 键 词：授时欺骗 机器学习 长短期记忆网络(LSTM) 欺骗检测 接收机钟差 

分 类 号：P228.4[天文地球—大地测量学与测量工程]