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Cyber-physical system

About: Cyber-physical system is a(n) research topic. Over the lifetime, 11096 publication(s) have been published within this topic receiving 162489 citation(s). The topic is also known as: CPS.

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Papers
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Open accessProceedings ArticleDOI: 10.1109/ISORC.2008.25
Edward A. Lee1Institutions (1)
05 May 2008-
Abstract: Cyber-Physical Systems (CPS) are integrations of computation and physical processes. Embedded computers and networks monitor and control the physical processes, usually with feedback loops where physical processes affect computations and vice versa. The economic and societal potential of such systems is vastly greater than what has been realized, and major investments are being made worldwide to develop the technology. There are considerable challenges, particularly because the physical components of such systems introduce safety and reliability requirements qualitatively different from those in general- purpose computing. Moreover, physical components are qualitatively different from object-oriented software components. Standard abstractions based on method calls and threads do not work. This paper examines the challenges in designing such systems, and in particular raises the question of whether today's computing and networking technologies provide an adequate foundation for CPS. It concludes that it will not be sufficient to improve design processes, raise the level of abstraction, or verify (formally or otherwise) designs that are built on today's abstractions. To realize the full potential of CPS, we will have to rebuild computing and networking abstractions. These abstractions will have to embrace physical dynamics and computation in a unified way.

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  • Figure 1. Abstraction layers in computing
    Figure 1. Abstraction layers in computing

3,020 Citations


Journal ArticleDOI: 10.1016/J.MFGLET.2014.12.001
Jay Lee1, Behrad Bagheri1, Hung-An Kao1Institutions (1)
Abstract: Recent advances in manufacturing industry has paved way for a systematical deployment of Cyber-Physical Systems (CPS), within which information from all related perspectives is closely monitored and synchronized between the physical factory floor and the cyber computational space. Moreover, by utilizing advanced information analytics, networked machines will be able to perform more efficiently, collaboratively and resiliently. Such trend is transforming manufacturing industry to the next generation, namely Industry 4.0. At this early development phase, there is an urgent need for a clear definition of CPS. In this paper, a unified 5-level architecture is proposed as a guideline for implementation of CPS.

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Topics: Cyber-physical system (60%), Industry 4.0 (55%), Analytics (52%)

2,716 Citations


Proceedings ArticleDOI: 10.1145/1837274.1837461
13 Jun 2010-
Abstract: Cyber-physical systems (CPS) are physical and engineered systems whose operations are monitored, coordinated, controlled and integrated by a computing and communication core. Just as the internet transformed how humans interact with one another, cyber-physical systems will transform how we interact with the physical world around us. Many grand challenges await in the economically vital domains of transportation, health-care, manufacturing, agriculture, energy, defense, aerospace and buildings. The design, construction and verification of cyber-physical systems pose a multitude of technical challenges that must be addressed by a cross-disciplinary community of researchers and educators.

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Topics: Cyber-physical system (60%), Grand Challenges (56%)

1,498 Citations


Open accessPosted Content
Abstract: Cyber-physical systems integrate computation, communication, and physical capabilities to interact with the physical world and humans. Besides failures of components, cyber-physical systems are prone to malignant attacks, and specific analysis tools as well as monitoring mechanisms need to be developed to enforce system security and reliability. This paper proposes a unified framework to analyze the resilience of cyber-physical systems against attacks cast by an omniscient adversary. We model cyber-physical systems as linear descriptor systems, and attacks as exogenous unknown inputs. Despite its simplicity, our model captures various real-world cyber-physical systems, and it includes and generalizes many prototypical attacks, including stealth, (dynamic) false-data injection and replay attacks. First, we characterize fundamental limitations of static, dynamic, and active monitors for attack detection and identification. Second, we provide constructive algebraic conditions to cast undetectable and unidentifiable attacks. Third, by using the system interconnection structure, we describe graph-theoretic conditions for the existence of undetectable and unidentifiable attacks. Finally, we validate our findings through some illustrative examples with different cyber-physical systems, such as a municipal water supply network and two electrical power grids.

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1,190 Citations


Open accessJournal ArticleDOI: 10.1109/TAC.2013.2266831
Abstract: Cyber-physical systems are ubiquitous in power systems, transportation networks, industrial control processes, and critical infrastructures. These systems need to operate reliably in the face of unforeseen failures and external malicious attacks. In this paper: (i) we propose a mathematical framework for cyber-physical systems, attacks, and monitors; (ii) we characterize fundamental monitoring limitations from system-theoretic and graph-theoretic perspectives; and (ii) we design centralized and distributed attack detection and identification monitors. Finally, we validate our findings through compelling examples.

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  • Fig. 6. Distributed detection of an output attack in the IEEE 118 system: The attacker compromises the measurements of all generators in area 1 from time 30s with a signal uniformly distributed in the interval [0, 0.5]. The residuals in Fig. 6(a) show that the attack is correctly detected, because the residual functions do not decay to zero. For the simulation, we run k = 100 iterations of the attack detection method. The plot in Fig. 6(b) represents the error of our waveform relaxation based filter (15) with respect to the corresponding decentralized filter. As predicted by Theorem 4.3, the error is convergent.
    Fig. 6. Distributed detection of an output attack in the IEEE 118 system: The attacker compromises the measurements of all generators in area 1 from time 30s with a signal uniformly distributed in the interval [0, 0.5]. The residuals in Fig. 6(a) show that the attack is correctly detected, because the residual functions do not decay to zero. For the simulation, we run k = 100 iterations of the attack detection method. The plot in Fig. 6(b) represents the error of our waveform relaxation based filter (15) with respect to the corresponding decentralized filter. As predicted by Theorem 4.3, the error is convergent.
  • Fig. 1. A block diagram illustration of prototypical attacks is here reported. In Fig. 1(a) the attacker corrupts the measurements y with the signal DKuK ∈ Im(C). Notice that in this attack the dynamics of the system are not considered. In Fig. 1(b) the attacker affects the output so that y(t) = y(x(0), [ūT uT]T, t) = y(x̃(0), 0, t). The covert attack in Fig. 1(c) is a feedback version of the replay attack, and it can be explained analogously. In Fig. 1(d) the attack is such that the unstable pole p is made unobservable.
    Fig. 1. A block diagram illustration of prototypical attacks is here reported. In Fig. 1(a) the attacker corrupts the measurements y with the signal DKuK ∈ Im(C). Notice that in this attack the dynamics of the system are not considered. In Fig. 1(b) the attacker affects the output so that y(t) = y(x(0), [ūT uT]T, t) = y(x̃(0), 0, t). The covert attack in Fig. 1(c) is a feedback version of the replay attack, and it can be explained analogously. In Fig. 1(d) the attack is such that the unstable pole p is made unobservable.
  • Fig. 5. For the IEEE 14 bus system in Fig. 5, if the voltage angle of one bus is measured exactly, then a cyber attack against the measurements data is always detectable by our dynamic detection procedure. In contrary, as shown in [9], a cyber attack may remain undetected by a static procedure if it compromises as few as four measurements.
    Fig. 5. For the IEEE 14 bus system in Fig. 5, if the voltage angle of one bus is measured exactly, then a cyber attack against the measurements data is always detectable by our dynamic detection procedure. In contrary, as shown in [9], a cyber attack may remain undetected by a static procedure if it compromises as few as four measurements.
  • Fig. 3. Partition of IEEE 118 bus system into 5 areas. Each area is monitored and operated by a control center. These control centers cooperate to estimate the state and to assess the functionality of the whole network.
    Fig. 3. Partition of IEEE 118 bus system into 5 areas. Each area is monitored and operated by a control center. These control centers cooperate to estimate the state and to assess the functionality of the whole network.
  • Fig. 2. Fig. 2(a) shows the WSSC power system with 3 generators and 6 buses. The numerical value of the network parameters can be found in [30]. The digraph associated with the network in Fig. 2(a). The self-loops of the vertices {δ1, δ2, δ3}, {ω1, ω2, ω3}, and {θ1, . . . , θ6} are not drawn. The inputs u1 and u2 affect respectively the bus b4 and the bus b5. The measured variables are the rotor angle and frequency of the first generator.
    Fig. 2. Fig. 2(a) shows the WSSC power system with 3 generators and 6 buses. The numerical value of the network parameters can be found in [30]. The digraph associated with the network in Fig. 2(a). The self-loops of the vertices {δ1, δ2, δ3}, {ω1, ω2, ω3}, and {θ1, . . . , θ6} are not drawn. The inputs u1 and u2 affect respectively the bus b4 and the bus b5. The measured variables are the rotor angle and frequency of the first generator.
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Topics: Cyber-physical system (57%)

1,143 Citations


Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202241
20211,264
20201,580
20191,576
20181,440
20171,336

Top Attributes

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Topic's top 5 most impactful authors

Xenofon Koutsoukos

34 papers, 733 citations

Paulo Leitão

21 papers, 279 citations

Bruce M. McMillin

19 papers, 180 citations

Danda B. Rawat

17 papers, 214 citations

Edward A. Lee

17 papers, 1.4K citations

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