Bibliographical review on cyber attacks from a control oriented perspective

Sánchez, Helem Sabina; Rotondo, Damiano; Escobet, Teresa; Puig, Vicenç; Quevedo, Joseba

doi:10.1016/j.arcontrol.2019.08.002

Cited by 106 publications

(60 citation statements)

References 262 publications

(319 reference statements)

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“…The former approach relies on data encryption techniques to protect critical sensor measurements, while the latter approach depends on secure anomaly identification methods to detect altered measurements. For a complete review of the effect of deception attacks on a CPS, see notable works in [4,42] for a review.…”

Section: Resilient Control Strategiesmentioning

confidence: 99%

Stochastic model predictive control framework for resilient cyber-physical systems: review and perspectives

Chen

Shi

2021

Phil. Trans. R. Soc. A.

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In the era of Industrial 4.0, the next-generation control system regards the cyber-physical system (CPS) as the core ingredient thanks to the comprehensive integration of physical systems, online computation, networking and control. A reliable, stable and resilient CPS should pledge robustness and safety. A significant concern in CPS development arises from security issues since the CPS is vulnerable to physical constraints, ubiquitous uncertainties and malicious cyber attacks. The integration of the stochastic model predictive control (MPC) framework and the resilient mechanism is a possible approach to guarantee robustness in the presence of stochastic uncertainties and enable resilience against cyber attacks. This review paper aims to offer a detailed overview of existing stochastic MPC algorithms and their CPS applications. More specifically, we first review existing stochastic MPC algorithms for both linear and nonlinear systems subject to probabilistic constraints. We then discuss how to extend the stochastic MPC framework to incorporate resilience mechanisms for constrained CPS under various malicious attacks. Finally, we present an architectural stochastic MPC-based framework for resilient CPS and identify future research challenges. This article is part of the theme issue ‘Towards symbiotic autonomous systems’.

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Section: Resilient Control Strategiesmentioning

confidence: 99%

Stochastic model predictive control framework for resilient cyber-physical systems: review and perspectives

Chen

Shi

2021

Phil. Trans. R. Soc. A.

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“…As an expansion of the study proposed in [ 19 ], the contributions of our study are as follows: When considering the flight as a part of a cyber physical system (CPS), many concerns that are related to the cybersecurity on the system have been raised, according to Sanchez et al in [ 20 ]. We proposed a series of analyses to extract an essential set of features from raw log-level flight data and validated that the set of features represents a distinct pattern between safe states and faulty states.…”

Section: Introductionmentioning

confidence: 99%

Unsupervised Fault Detection on Unmanned Aerial Vehicles: Encoding and Thresholding Approach

Park

Kim

2021

Sensors

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Unmanned Aerial Vehicles are expected to create enormous benefits to society, but there are safety concerns in recognizing faults at the vehicle’s control component. Prior studies proposed various fault detection approaches leveraging heuristics-based rules and supervised learning-based models, but there were several drawbacks. The rule-based approaches required an engineer to update the rules on every type of fault, and the supervised learning-based approaches necessitated the acquisition of a finely-labeled training dataset. Moreover, both prior approaches commonly include a limit that the detection model can identify the trained type of faults only, but fail to recognize the unseen type of faults. In pursuit of resolving the aforementioned drawbacks, we proposed a fault detection model utilizing a stacked autoencoder that lies under unsupervised learning. The autoencoder was trained with data from safe UAV states, and its reconstruction loss was examined to distinguish the safe states and faulty states. The key contributions of our study are, as follows. First, we presented a series of analyses to extract essential features from raw UAV flight logs. Second, we designed a fault detection model consisting of the stacked autoencoder and the classifier. Lastly, we validated our approach’s fault detection performance with two datasets consisting of different types of UAV faults.

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“…In addition, CPS attacks are difficult to trace, classify or identify the original threat, which may move or spread, and target multiple components of the system. For this reason, research on cyber attacks and secure control has found increasing interest [3].…”

Section: Introductionmentioning

confidence: 99%

“…Then, it is presented the mathematical model for different adversary models such as zero-dynamics attack, covert attack, false data injection attack and replay attack. In addition, Sanchez et al [3] provides a detailed bibliographic review of cyber-physical attacks given illustrative examples.…”

Section: Introductionmentioning

confidence: 99%

Switched-Based Resilient Control of Cyber-Physical Systems

Segovia-Ferreira¹,

Rubio‐Hernan²,

Cavalli³

et al. 2020

IEEE Access

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We present a control-theoretic approach to achieve Cyber-Physical Systems (CPS) resilient designs. We assume situations in which the CPS must maintain the correct operation of a set of crucial functionalities despite ongoing adversarial misbehavior. The approach is based on a moving target defense paradigm, driven by a linear switching of state-space matrices, and applied at both the physical and network layers of a networked-control system. We show that the final system maintains stability. We also evaluate, via simulation, a step-by-step procedure that takes a transfer function, representing the dynamics of the physical process. As a result, we obtain a resilient CPS design structured around a topology of decentralized controllers. Results show that the obtained approach is both innovative and promising.

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Bibliographical review on cyber attacks from a control oriented perspective

Cited by 106 publications

References 262 publications

Stochastic model predictive control framework for resilient cyber-physical systems: review and perspectives

Stochastic model predictive control framework for resilient cyber-physical systems: review and perspectives

Unsupervised Fault Detection on Unmanned Aerial Vehicles: Encoding and Thresholding Approach

Switched-Based Resilient Control of Cyber-Physical Systems

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