UASTrustChain: A Decentralized Blockchain- Based Trust Monitoring Framework for Autonomous Unmanned Aerial Systems
UASTrustChain: A Decentralized Blockchain- Based Trust Monitoring Framework for Autonomous Unmanned Aerial Systems
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DOI：
10.1109/access.2020.3044844
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发表时间：
2020
期刊：
影响因子：
3.9
通讯作者：
Mahsa Keshavarz;Mohammed Gharib;F. Afghah;J. Ashdown
中科院分区：
文献类型：
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作者：
Mahsa Keshavarz;Mohammed Gharib;F. Afghah;J. Ashdown
无人机系统（UAS）容易受到多种网络物理攻击，这会降低网络性能，并可能对无人机（UAV）或其周围环境造成损害。在本文中，我们提出了UASTrustChain，一个基于区块链时间戳系列的信任管理框架。我们考虑一个模型系统，由许多自主无人机组成，其行为由一组分布式观察者（DO）定期监控。由于大多数网络攻击都会导致无人机运行中断或偏离原始路径，因此 DO 会根据无人机的轨迹以及成功任务的数量来跟踪无人机的行为。 DO 计算每架无人机的相对信任分数，并将这些分数保存在透明、可靠、安全和开放的账本中。该框架可以实时检测无人机的异常行为，进一步检测受损的分布式观察者（如果有）。所提出的框架还可以区分由真实攻击引起的异常活动和由恶劣环境条件引起的异常活动。我们通过进行大量的模拟实验来评估所提出的框架的功能和准确性。我们的模拟结果表明，所提出的信任模型可以检测受损的分布式观察者并减弱它们对无人机信任评分的影响。结果进一步表明该系统检测恶意无人机的能力，这些无人机可能受到各种网络物理攻击。
Unmanned aerial systems (UASs) are prone to several cyber-physical attacks, which decrease the performance of the network and may cause damage to the unmanned aerial vehicles (UAVs) or their surrounding environment. In this paper, we propose UASTrustChain, a trust management framework based on Blockchain time-stamped series. We consider a system of models, consists of a number of autonomous UAVs, whose behaviors are regularly monitored by a set of distributed observers (DOs). Since most cyber attacks cause interruption in the operations of UAVs or deviation from their original path, the DOs keep track of the UAVs’ behavior in terms of their trajectory, as well as the number of their successful tasks. The DOs calculate a relative trust score for each UAV and keep these scores in a transparent, reliable, secure and open ledger. This framework can detect UAVs’ abnormal behavior in a real-time manner further to detect the compromised distributed observers, if any. The proposed framework could also distinguish abnormal activities due to real attacks from those caused by harsh environmental conditions. We evaluate the proposed framework for its functionality and accuracy by performing extensive simulation experiments. Our simulation results show that the proposed trust model can detect compromised distributed observers and fades their effect on the UAVs trust scores. Results further show the ability of the system in detecting malicious UAVs, which can be under various cyber-physical attacks.