基于TriLSTM-SVDD的ADS-B欺骗数据检测方法

An ADS-B Spoofing Data Detection Method Based on TriLSTM-SVDD Model

广播式自动相关监视(ADS-B)协议公开、无认证措施等特点,使其易受消息修改攻击。首先,分析了攻击者攻击意图与攻击路径选择的关联性;然后,为了应对通过1090ES链路、机载网络等实施的消息修改攻击,提出了经特征处理的TriLSTM-SVDD模型进行欺骗数据检测。仿真结果表明,TriLSTM模型预测误差显著小于LSTM模型,TriLSTM-SVDD模型则以98.9%的准确率识别出0.01°的纬度值偏差、0.02°的经度值偏差和50 m的高度值偏差。

Automatic Dependent Surveillance-Broadcast(ADS-B)has such features as open protocols and no authentication measures,which makes it vulnerable to message modification attacks.Firstly,the correlation between attacker intention and attack path selection is analyzed.Then,the TriLSTM-SVDD model with feature processing is proposed for spoofing data detection,so as to defend against message modification attacks implemented through 1090ES,onboard network or other attack paths.The experimental results show that the prediction error of TriLSTM model is significantly smaller than that of LSTM model,and the TriLSTM-SVDD model can identify latitude value deviations of 0.01°,longitude value deviations of 0.02°and height value deviations of 50 m with 98.9%accuracy.