Cyber Attack Detection in Platoon-Based Vehicular Networked Control Systems
Cyber Attack Detection in Platoon-Based Vehicular Networked Control Systems
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DOI：
10.1109/isie.2018.8433814
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发表时间：
2018-06
期刊：
影响因子：
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通讯作者：
I. Mousavinejad;Fuwen Yang;Q. Han;Quanwei Qiu;L. Vlacic
中科院分区：
文献类型：
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作者：
I. Mousavinejad;Fuwen Yang;Q. Han;Quanwei Qiu;L. Vlacic
研究了基于排的车载网络控制系统中的网络攻击检测问题。在这样的系统中，车辆之间的信息通过共享的无线通信网络传输，并且每个车辆还可以访问由本地传感器测量的其自身的信息。这类系统极易受到网络攻击，因此，需要妥善解决网络安全问题，以确保系统的安全。在各种网络安全方面，可靠的攻击检测至关重要，因为及时检测网络攻击的能力可以减少对系统的损害。因此，我们提出了一种网络攻击检测算法，该算法能够检测违反测量和控制命令数据的攻击。该算法基于椭球集员滤波方法，该方法由两个集合组成：预测椭球集合和通过测量数据更新预测椭球集合而计算的估计椭球集合。检测方法取决于由滤波器计算的这两个集合之间的交集的存在。对一些可能的网络攻击的仿真结果证明了该方法的有效性。
This paper is concerned with cyber attack detection problem in a platoon-based vehicular networked control system. In such a system, the information among vehicles is transmitted through a shared wireless communication network and also each vehicle has access to its own information measured by local sensors. These kind of systems are highly vulnerable to cyber attacks and therefore, cyber-security issues need to be properly addressed to ensure the safety of the systems. Among various cyber-security aspects, reliable attack detection is of utmost importance as the ability to detect cyber attacks in a timely manner can reduce the damage to the systems. Therefore, we present a cyber attack detection algorithm that is capable of detecting attacks violating both measurements and control command data. This algorithm is based on an ellipsoidal set-membership filtering approach which consists of two sets: prediction ellipsoid set and an estimation ellipsoid set calculated through updating the prediction ellipsoid set with the measurement data. The detection method depends on the existence of intersection between these two sets computed by the filter. Simulation results for some possible cyber attacks are provided to demonstrate the effectiveness of the proposed method.