2018 · 16 citations · 12 references
ComputingComputer ScienceCybersecurityComputer SecurityCyber-physical SystemsSecurity ArchitectureCyber-physical SecurityKalman FilteringSecurity SystemsThreat DetectionVehicle CybersecurityAttack Detection In Cyber-physical SystemsCyber-physical Attack DetectionCyber-physical Attack ResilienceCyber-physical System SecurityReplayReplay Attack DetectionReplay AttacksUnmanned Ground Vehicles
This project develops techniques to protect against sensor attacks on cyber-physical systems. Specifically, a resilient version of the Kalman filtering technique accompanied with a watermarking approach is proposed to detect cyber-attacks and estimate the correct state of the system. The defense techniques are used in conjunction and validated on two case studies: i) an unmanned ground vehicle (UGV) in which an attacker alters the reference angle and ii) a Cube Satellite (CubeSat) in which an attacker modifies the orientation of the satellite degrading its performance. Based on this work, we show that the proposed techniques in conjunction achieve better resiliency and defense capability than either technique alone against spoofing and replay attacks.
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Attack models and scenarios for networked control systems
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False data injection attacks against state estimation in wireless sensor networks
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