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Cyber-physical system

About: Cyber-physical system is a research topic. Over the lifetime, 11096 publications have been published within this topic receiving 162489 citations. The topic is also known as: CPS.


Papers
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Journal ArticleDOI
TL;DR: Distributed tracking problem for complex dynamical networks with Lipschitz-type nonlinear dynamics under the framework of cyber-physical systems is investigated and Lyapunov stability theory is utilizing to check whether final consensus tracking can be achieved against frequently malicious attacks.
Abstract: Distributed tracking problem for complex dynamical networks with Lipschitz-type nonlinear dynamics under the framework of cyber-physical systems is investigated. Due to practical limitations in some circumstances, the states of the agents are usually unavailable for controllers, so distributed observers used to reconstruct the states of nodes are needed, which will be first designed. Differing from other studies of observer-based control problems for complex dynamical networks and multi-agent systems, it considers here the scenario that the communication channels for controllers and observers may be subjected to frequently malicious attacks, which will destroy the communication links and result in disconnected topologies of the communication networks. It is assumed that the impacts of attacks on different communication networks are different and independent. New security control strategies are proposed and analyzed. An algorithm to properly select the feedback gain matrices and coupling strengths is presented. By utilizing the Lyapunov stability theory, sufficient conditions are derived to check whether final consensus tracking can be achieved against such attacks. Finally, a simulation example comparing the security control and uncontrolled scenarios is demonstrated to show the effectiveness of the theoretical results.

89 citations

Journal ArticleDOI
TL;DR: This survey paper presents an overview of research efforts on the integration of cyber-physical systems with cloud computing and categorizes them into three areas: (1) remote brain, (2) big data manipulation, (3) and virtualization.

89 citations

Journal ArticleDOI
TL;DR: A Security-Aware Efficient Data Sharing and Transferring (SA-EAST) model is proposed, which is designed for securing cloud-based ITS implementations and aims to obtain secure real-time multimedia data sharing and transferring.
Abstract: The expected advanced network explorations and the growing demand for mobile data sharing and transferring have driven numerous novel applications in Cyber-Physical Systems (CPSs), such as Intelligent Transportation Systems (ITSs). However, current ITS implementations are restricted by the conflicts between security and communication efficiency. Focusing on this issue, this article proposes a Security-Aware Efficient Data Sharing and Transferring (SA-EAST) model, which is designed for securing cloud-based ITS implementations. In applying this approach, we aim to obtain secure real-time multimedia data sharing and transferring. Our experimental evaluation has shown that our proposed model provides an effective performance in securing communications for ITS.

89 citations

Journal ArticleDOI
Fangyu Li1, Yang Shi1, Aditya Shinde1, Jin Ye1, Wen-Zhan Song1 
TL;DR: This is the first attempt to detect and identify IoT cyber and physical attacks based on energy auditing and analytics-based IoT monitoring mechanism using the energy meter readings and proposes a disaggregation-aggregation architecture.
Abstract: Internet of Things (IoT) are vulnerable to both cyber and physical attacks. Therefore, a cyber-physical security system against different kinds of attacks is in high demand. Traditionally, attacks are detected via monitoring system logs. However, the system logs, such as network statistics and file access records, can be forged. Furthermore, existing solutions mainly target cyber attacks. This paper proposes the first energy auditing and analytics-based IoT monitoring mechanism. To our best knowledge, this is the first attempt to detect and identify IoT cyber and physical attacks based on energy auditing. Using the energy meter readings, we develop a dual deep learning (DL) model system, which adaptively learns the system behaviors in a normal condition. Unlike the previous single DL models for energy disaggregation, we propose a disaggregation-aggregation architecture. The innovative design makes it possible to detect both cyber and physical attacks. The disaggregation model analyzes the energy consumptions of system subcomponents, e.g., CPU, network, disk, etc., to identify cyber attacks, while the aggregation model detects the physical attacks by characterizing the difference between the measured power consumption and prediction results. Using energy consumption data only, the proposed system identifies both cyber and physical attacks. The system and algorithm designs are described in detail. In the hardware simulation experiments, the proposed system exhibits promising performances.

88 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023831
20221,955
20211,283
20201,586
20191,576
20181,441