A framework for detection of sensor attacks on small unmanned aircraft systems
A framework for detection of sensor attacks on small unmanned aircraft systems
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DOI：
10.1109/icuas.2017.7991465
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发表时间：
2017-06
期刊：
影响因子：
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通讯作者：
D. Muniraj;M. Farhood
中科院分区：
文献类型：
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作者：
D. Muniraj;M. Farhood
本文中介绍的工作是为小型无人机系统（UAS）设计安全自动驾驶仪的整体努力的一部分，该自动驾驶仪可以抵御来自网络和物理层的恶意攻击。本文主要研究了小型无人机传感器恶意攻击的识别问题。提出了一个框架，其中统计分析技术在概率设置中用于检测传感器攻击。本文详细介绍了异常检测器和贝叶斯网络的设计。在整个论文中，使用了一个涉及检测GPS欺骗攻击的案例研究来说明所提出的方法。异常探测器是基于模拟数据集设计的，并根据在小型固定翼无人机平台上进行的飞行测试进行重新调整。研究了探测器在不同外部干扰下的性能，并得出了结论。
The work presented in this paper is part of an overall effort to design a secure autopilot, resilient against malicious attacks on both the cyber and physical layers, for a small unmanned aircraft system (UAS). This paper specifically deals with identification of malicious attacks on the sensors of a small UAS. A framework is presented wherein techniques from statistical analysis are used in a probabilistic setting to detect sensor attacks. The paper describes in detail the design of anomaly detectors and the Bayesian network. A case study involving detection of a spoofing attack on the GPS is used throughout the paper to illustrate the proposed approach. The anomaly detectors are designed based on a simulation dataset, and are re-tuned based on flight tests conducted on a small fixed-wing UAS platform. The performances of the detectors are studied under different external disturbances and conclusions are drawn.