ADS-B攻击数据弹性恢复方法

A Resilient Recovery Method on ADS-B Attack Data

为了对自动广播相关监视(ADS-B)攻击数据进行弹性恢复,确保空情态势感知信息的持续可用性,该文提出针对ADS-B攻击数据的弹性恢复方法。基于前置的攻击检测机制,获取当前ADS-B量测数据序列和预测数据序列,并在此基础上构建偏差数据序列、差分数据序列和邻近密度数据序列。依托偏差数据构建恢复向量,依托差分数据挖掘攻击数据的时序特性,依托邻近密度数据挖掘攻击数据的空间特性。通过整合3种数据序列构建弹性恢复策略并确定恢复终止点,实现对攻击影响的弱化,将ADS-B攻击数据向正常数据方向进行定向恢复。通过对6种典型攻击样式的实验分析,证明该弹性恢复方法能够有效恢复ADS-B攻击数据,削弱数据攻击对监视系统的影响。

In order to conduct effective resilient recovery on Automatic Dependent Surveillance-Broadcast(ADS-B)attack data and ensure the continuous availability of air traffic situation awareness,a resilient recovery method on ADS-B attack data is proposed.Based on attack detection strategies,the measurement and prediction sequences of ADS-B data are obtained to set up deviation data,differential data and neighbor density data sequences,which are designed to construct recovery vectors,mine the temporal correlations and the spatial correlations respectively.The selected data sequences are integrated to accomplish the whole recovery method and decide the end point of recovery.The method is applied to elinimating attack effects and recovering the attack data towards normal data.According to the results of experiments on six classical attack patterns,the proposed method is effective on recovering attack data and eliminating the attack impacts.