Abstract
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 article, 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.
Highlights
U NMANNED aerial vehicles (UAVs) are being more widely used in several civilian and military operations including remote sensing, surveillance, package delivery, disaster relief and medical services [1]–[7]
We show how our algorithm is able to differentiate between the UAVs’ abnormal behavior when they are under an attack and when they are operating under harsh environmental conditions
We proposed UASTrustChain, a general decentralized real-time trust monitoring framework to score the trustworthiness of UAVs and detect the malicious ones
Summary
U NMANNED aerial vehicles (UAVs) are being more widely used in several civilian and military operations including remote sensing, surveillance, package delivery, disaster relief and medical services [1]–[7]. Due to their unique features such as high-mobility, ease of deployment, and their ability to hover, UAVs can provide services including urgent Internet and communication services in time-critical missions or natural disasters [8], [9]. The UAVs are vulnerable to several attacks, including cyberattacks such as false data injection [10], physical attacks such as targeting the UAVs using firearms [11], and cyber-physical attacks such as GPS spoofing [12].
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