A Survey on Cyber–Physical Systems Security

Yu, Zhenhua; Gao, Hongxia; Cong, Xuya; Wu, Naiqi; Song, Houbing

doi:10.1109/jiot.2023.3289625

Cited by 24 publications

(4 citation statements)

References 143 publications

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“…Actually, in the text of the analysis of real-world data, besides for change point models, several ways of analyzing financial time series are possible, such as Cherstvy [35], Yu [36], Kantz [37], who introduced three strategies for the analysis of financial time series based on time-averaged observables, which contained the time-averaged mean-squared displacement as well as the aging and delay time methods for the varying fractions of the financial time series. They found that the observed features of the financial time series dynamics agree well with our analytical results for the time-averaged measurables for geometric Brownian motion, underlying the famed Black-Scholes-Merton model.…”

Section: Empirical Applicationsmentioning

confidence: 99%

Modified Block Bootstrap Testing for Persistence Change in Infinite Variance Observations

Zhang,

Jin,

2024

Mathematics

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This paper investigates the properties of the change in persistence detection for observations with infinite variance. The innovations are assumed to be in the domain of attraction of a stable law with index κ∈(0,2]. We provide a new test statistic and show that its asymptotic distribution under the null hypothesis of non-stationary I(1) series is a functional of a stable process. When the change point in persistence is not known, the consistency is always given under the alternative, either from stationary I(0) to non-stationary I(1) or vice versa. The proposed tests can be used to identify the direction of change and do not over-reject against constant I(0) series, even in relatively small samples. Furthermore, we also consider the change point estimator which is consistent and the asymptotic behavior of the test statistic in the case of near-integrated time series. A block bootstrap method is suggested to determine critical values because the null asymptotic distribution contains the unknown tail index, which results in critical values depending on it. The simulation study demonstrates that the block bootstrap-based test is robust against change in persistence for heavy-tailed series with infinite variance. Finally, we apply our methods to the two series of the US inflation rate and USD/CNY exchange rate, and find significant evidence for persistence changes, respectively, from I(0) to I(1) and from I(1) to I(0).

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Section: Empirical Applicationsmentioning

confidence: 99%

Modified Block Bootstrap Testing for Persistence Change in Infinite Variance Observations

Zhang,

Jin,

2024

Mathematics

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“…These outliers usually do not accurately reflect the environmental data and can affect the accuracy of the prediction model to some extent. It may also lead to external attacks on the entire network, affecting the overall operational security [32]. To enhance the precision of prediction algorithms, the availability of dependable initial data is paramount to the efficacy of these algorithms.…”

Section: ) Data Pre-processingmentioning

confidence: 99%

An Improved Data Fusion Algorithm Based on Cluster Head Election and Grey Prediction

Wang,

Sun

et al. 2024

IEEE Access

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In traditional Wireless Sensor Network routing protocols, data collected through timed interval sensing tends to have high temporal redundancy, which leads to unnecessary energy drain. To alleviate this problem and enable sensor networks to save energy to some extent, a practical solution is to utilize predictionbased data fusion methods. To this end, this paper first proposes a Low Energy Adaptive Clustering Hierarchy-Energy-Kopt-N algorithm, an optimization algorithm explicitly designed to address the clusterhead election phase of the Low Energy Adaptive Clustering Hierarchy protocol. Then, a data collection model using data prediction techniquesthe Grey Data Prediction Model is formatted. Combining these improvements, a new data fusion algorithm that relies on data prediction, Grey-Clusters-Leach (GCL), is proposed. Simulation experiments demonstrate that the network energy drain of the GCL algorithm is reduced by 35%, 21.5%, and 20%, and the network operation critical period life is extended by 35%, 22%, and 5% compared to the LEACH, LEACH-E, EQDC and SEP algorithms, respectively. GCL can effectively manage the size and number of clusters and reduce the number of packet transmissions by 20% through data prediction.INDEX TERMS Wireless sensor network, cluster head election, grey model, data fusion

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“…The concept of CPS emerged from the integration of embedded computer and communication technologies into various physical domains and sectors. It aims to monitor and control these physical processes effectively [10][11][12]. Many of these systems offer symmetry properties.…”

Section: Introductionmentioning

confidence: 99%

Design Procedure for Real-Time Cyber–Physical Systems Tolerant to Cyberattacks

Paredes,

Martínez Castro,

González Potes

et al. 2024

Symmetry

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Modern industrial automation supported by Cyber–Physical Systems (CPSs) requires high flexibility, which is achieved through increased interconnection between modules. This interconnection introduces a layer of symmetry into the design and operation of CPSs, balancing the distribution of tasks and resources across the system and streamlining the flow of information. However, this adaptability also exposes control systems to security threats, particularly through novel communication links that are vulnerable to cyberattacks. Traditional strategies may have limitations in these applications. This research proposes a design approach for control applications supported by CPSs that incorporates cyberattack detection and tolerance strategies. Using a modular and adaptive approach, the system is partitioned into microservices for scalability and resilience, allowing structural symmetry to be maintained. Schedulability assessments ensure that critical timing constraints are met, improving overall system symmetry and performance. Advanced cyberattack detection and isolation systems generate alarms and facilitate rapid response with replicas of affected components. These replicas enable the system to recover from and tolerate cyberattacks, maintaining uninterrupted operation and preserving the balanced structure of the system. In conclusion, the proposed approach addresses the security challenges in CPS-based control applications and provides an integrated and robust approach to protect industrial automation systems from cyber threats. A case study conducted at a juice production facility in Colima, México, demonstrated how the architecture can be applied to complex processes such as pH control, from simulation to industrial implementation. The study highlighted a plug-and-play approach, starting with component definitions and relationships, and extending to technology integration, thereby reinforcing symmetry and efficiency within the system.

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A Survey on Cyber–Physical Systems Security

Abstract: County (UMBC)ScholarWorks@UMBC digital repository on the Maryland Shared Open Access (MD-SOAR) platform.

Cited by 24 publications

References 143 publications

Modified Block Bootstrap Testing for Persistence Change in Infinite Variance Observations

Modified Block Bootstrap Testing for Persistence Change in Infinite Variance Observations

An Improved Data Fusion Algorithm Based on Cluster Head Election and Grey Prediction

Design Procedure for Real-Time Cyber–Physical Systems Tolerant to Cyberattacks

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