Security of unmanned aerial vehicles: Dynamic state estimation under cyber-physical attacks

Petnga, Leonard; Xu, Huan

doi:10.1109/icuas.2016.7502663

Cited by 17 publications

(6 citation statements)

References 12 publications

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“…where ( 23) is obtained by using 𝛾 n = 𝛾 * n in (9) under Framework AD-AI, and ( 23) is obtained by Jensen's Inequality in [24, Lemma 1 (h)] and noting the fact that g(X , …) is monotonically increasing with respect to X .…”

Section: 𝔼[Pmentioning

confidence: 99%

Secure LQG control for a Quadrotor under false data injection attacks

Lin

Sun

Cai

et al. 2022

IET Control Theory & Appl

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The linear quadratic Gaussian (LQG) control for a quadrotor unmanned aerial vehicle (UAV) under false data injection attacks is studied. The LQG control depends on optimal state estimation, while this type of attacks makes the optimal state estimation unimplementable in practice. To address this problem, the authors prose a framework to detect attacks and then augment the information for controller design. Based on this framework, the LQG control is designed and a sufficient condition for the security of the closed‐loop control system is given. Finally, the LQG controller is applied to a quadrotor UAV, and some experiments are carried out to illustrate its effectiveness.

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Section: 𝔼[Pmentioning

confidence: 99%

Secure LQG control for a Quadrotor under false data injection attacks

Lin

Sun

Cai

et al. 2022

IET Control Theory & Appl

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“…In [19], Berntorp et al gave a high-level control architecture of autonomous vehicles, which includes motion planning, vehicle control, and actuator control along with sensing and mapping as major blocks. Petnga et al discuss a high-level architecture of a UAV reflecting the interactions between cyber (command, control, communication) and physical (sensors and actuators) components of these systems [20]. Based on these studies, we identify three major modules common to popular AS i) perception, ii) cognition, and iii) control.…”

Section: Autonomous System (As) Architecturementioning

confidence: 99%

A Non-Cooperative Game based Model for the Cybersecurity of Autonomous Systems

Jahan

Sun

Niyaz

2020

2020 IEEE Security and Privacy Workshops (SPW)

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Autonomous systems (AS) would soon revolutionize the way we live and work. The days are not so far when these systems, from delivery drones to driverless cars, would be seen around us. These systems are connected and rely heavily on the communication network for the information exchange, hence prone to several attacks. Human lives will be at risk if these systems are compromised. Cybersecurity modeling and attack analysis of AS needs the utmost attention of the research community. Primarily, a typical AS has three modules -perception, cognition, and control -and each one of them comes with their own vulnerabilities. In this work, we propose a new AS architecture that may prove useful in AS cybersecurity modeling. We also model the attacks on them, and defense mechanisms applied to these modules using a non-cooperative non-zero sum game. Finally, we solve this game to obtain optimal strategies to maintain a secure system state.

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“…Another way to detect that a jamming attack is happening is by setting a window and checking the rate of collision; if the rate becomes higher than normal, this would indicate that the system is under a jamming attack. The operator can then block the source of jamming attack [13]. Or adjust the transmission rate in order to contain jamming interference (Li et al 2007).…”

Section: Safeguards Ensuring Availabilitymentioning

confidence: 99%