Academic literature on the topic 'Cyber-Physical Systems (CPSs)'
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Journal articles on the topic "Cyber-Physical Systems (CPSs)"
Yan, He Hua, Jia Fu Wan, and Hui Suo. "Adaptive Resource Management for Cyber-Physical Systems." Applied Mechanics and Materials 157-158 (February 2012): 747–51. http://dx.doi.org/10.4028/www.scientific.net/amm.157-158.747.
Full textSadiku, Matthew N. O., Yonghui Wang, Suxia Cui, and Sarhan M. Musa. "Cyber-Physical Systems: A Literature Review." European Scientific Journal, ESJ 13, no. 36 (December 31, 2017): 52. http://dx.doi.org/10.19044/esj.2017.v13n36p52.
Full textHe, Xudong, Zhijiang Dong, Heng Yin, and Yujian Fu. "A Framework for Developing Cyber-Physical Systems." International Journal of Software Engineering and Knowledge Engineering 27, no. 09n10 (November 2017): 1361–86. http://dx.doi.org/10.1142/s0218194017400010.
Full textAbrahamsson, Pekka, Goetz Botterweck, Hadi Ghanbari, Martin Gilje Jaatun, Petri Kettunen, Tommi J. Mikkonen, Anila Mjeda, et al. "Towards a Secure DevOps Approach for Cyber-Physical Systems." International Journal of Systems and Software Security and Protection 11, no. 2 (July 2020): 38–57. http://dx.doi.org/10.4018/ijsssp.2020070103.
Full textZeadally, Sherali, Teodora Sanislav, and George Dan Mois. "Self-Adaptation Techniques in Cyber-Physical Systems (CPSs)." IEEE Access 7 (2019): 171126–39. http://dx.doi.org/10.1109/access.2019.2956124.
Full textFeng, Jun, Laurence T. Yang, Yuxiang Zhu, Nicholaus J. Gati, and Yijun Mo. "Blockchain-enabled Tensor-based Conditional Deep Convolutional GAN for Cyber-physical-Social Systems." ACM Transactions on Internet Technology 21, no. 2 (June 21, 2021): 1–17. http://dx.doi.org/10.1145/3404890.
Full textKumar, Amit. "Cyber Physical Systems (CPSs) – Opportunities and Challenges for Improving Cyber Security." International Journal of Computer Applications 137, no. 14 (March 22, 2016): 19–27. http://dx.doi.org/10.5120/ijca2016908877.
Full textRajamäki, Jyri, and Rauno Pirinen. "Design science research towards resilient cyber-physical eHealth systems." Finnish Journal of eHealth and eWelfare 9, no. 2-3 (May 21, 2017): 203. http://dx.doi.org/10.23996/fjhw.61000.
Full textZivi, Edwin. "Teaching Cyber-Physical Systems." Mechanical Engineering 139, no. 03 (March 1, 2017): S3—S8. http://dx.doi.org/10.1115/1.2017-mar-4.
Full textJacobs, Nicholas, Shamina Hossain-McKenzie, and Adam Summers. "Modeling Data Flows with Network Calculus in Cyber-Physical Systems: Enabling Feature Analysis for Anomaly Detection Applications." Information 12, no. 6 (June 19, 2021): 255. http://dx.doi.org/10.3390/info12060255.
Full textDissertations / Theses on the topic "Cyber-Physical Systems (CPSs)"
Kavuri, Ajay Krishna Teja. "Information Centric Strategies for Scalable Data Transport in Cyber Physical Systems (CPSs)." Thesis, West Virginia University, 2017. http://pqdtopen.proquest.com/#viewpdf?dispub=10276185.
Full textCyber-Physical Systems (CPSs) represent the next generation of computing that is ubiquitous, wireless and intelligent. These networked sens- ing systems are at the intersection of sensing, communication, control, and computing [16]. Such systems will have applications in numerous elds such as vehicular systems and transportation, medical and health care systems, smart homes and buildings, etc. The proliferation of such sensing systems will trigger an exponential increase in the computational devices that exchange data over existing network infrastructure.
Transporting data at scale in such systems is a challenge [21] mainly due to the underlying network infrastructure which is still resource con- strained and bandwidth-limited. Eorts have been made to improve the network infrastructure [5] [2] [15]. The focus of this thesis is to put forward information-centric strategies that optimize the data transport over existing network infrastructure.
This thesis proposes four dierent information-centric strategies: (1) Strategy to minimize network congestion in a generic sensing system by estimating data with adaptive updates, (2) An adaptive information exchange strategy based on rate of change of state for static and mobile networks, (3) Spatio-temporal strategy that maintains spatial resolution by reducing redundant transmissions, (4) Proximity-dependent data transfer strategy to ensure most updated information in high-density regions. Each of these strategies is experimentally veried to optimize the data transport in their respective setting.
Guermazi, Sahar. "Model-driven co-simulation of Cyber-Physical Systems." Thesis, Université Paris-Saclay (ComUE), 2017. http://www.theses.fr/2017SACLS333/document.
Full textCyber Physical Systems (CPS) are integrations of physical and computational components. CPS are difficult to model and verify because the heterogeneous nature of their components requires many different modeling formalisms. The global verification of the system can be achieved by co-simulation. FMI standard offers a standard interface to couple two or more simulators in a co-simulation environment, known as master. This latter is responsible for providing an algorithm with efficient orchestration and synchronization of the involved components, known as FMUs. However, FMI was originally intended for co-simulation of physical processes, with limited support for formalisms such as DE and Dara-Flow, even if this kind of formalisms are commonly used to model the logic of software parts of a system. In particular, while UML is the reference standard for software modeling and is very commonly used in industry, none of the present-day FMI-based co-simulation solutions consider UML models. Our thesis is that system engineering in general would greatly benefit from the consideration of UML in FMI-based co-simulation approach. It would indeed enable a significant number of software designers to evaluate the behavior of their software components in their simulated environment, as soon as possible in their development processes, and therefore make early and better design decisions. It would also open new interesting perspectives for CPS system engineers, by allowing them to consider a widely used modeling language for the software parts of their systems. In this context, the objective of this work is to define an FMI-based co-simulation environment for CPS with integration of UML models for software part. Our contribution is twofold: locally at the level of UML models, and globally at the master level. At the local level, we set up an incremental approach where we address different kinds of discrete event systems characterizing the computational components. We base our proposals on OMG standards fUML and PSCS which define precise execution semantics for a subset of UML. They provide an interesting and formal basis for the integration of UML models in CPSs co-simulation approaches. For each kind of system, we first identify a set of rules to model it with UML and potential extensions to fUML in case where execution semantics of the required UML elements are not defined by fUML. Then, at the global level, we propose a master algorithm for each kind of systems. The proposed masters take into account not only external and internal dependencies between components and their capabilities, but also and especially their models of time. They rely on adaptation of fUML semantics to that of the FMI API. Based on these adaptations, the master algorithm is able both to propagate data between components and to trigger them at the correct points of time. The approach is illustrated with use cases from the energy domain where the purpose is to verify energy management strategies defined as software components at different levels of the control module of an energy system
Meno, Emma Margaret. "Neural Cryptanalysis for Cyber-Physical System Ciphers." Thesis, Virginia Tech, 2021. http://hdl.handle.net/10919/103373.
Full textMaster of Science
Cryptanalysis is the process of systematically measuring the strength of ciphers, algorithms used to secure data and information. Through encryption, a cipher is applied to an original message or plaintext to generate muddled message or ciphertext. The inverse of this operation, translating ciphertext back into plaintext, is decryption. Symmetric ciphers only require one shared secret key that is used during for both encryption and decryption. Machine learning is a data analysis method that automates computers to learn certain data properties, which can be used to predict outputs given a set of inputs. Neural networks are one type of machine learning used to uncover relationships, chaining a series of nodes together that individually perform some operations to determine correlations. The topic of this work is neural cryptanalysis, a new approach to evaluate cipher strength relying on machine learning. In this method, the goal is to "learn" the ciphers, using machine learning to predict what the ciphertext will be for an inputted plaintext. This is done by training the networks on plaintext/ciphertext pairs to extract meaningful relationships. If a cipher is easier to predict, it is easier to crack and thus less secure. In this work, neural cryptanalysis was applied to different real-world symmetric ciphers to rank their relatively security. This technique worked best on analyzing smaller components of the cipher algorithms rather than the entire cipher, as the ciphers were complex and the neural networks were simpler.
Graziano, Timothy Michael. "Establishment of a Cyber-Physical Systems (CPS) Test Bed to Explore Traffic Collision Avoidance System (TCAS) Vulnerabilities to Cyber Attacks." Thesis, Virginia Tech, 2021. http://hdl.handle.net/10919/104624.
Full textMaster of Science
Traffic Collision Avoidance Systems (TCAS), or Airborne Collision Avoidance Systems ACAS), are safety-critical systems required by the Federal Aviation Administration (FAA) in commercial aircraft. They work by sending queries to surrounding aircraft in the form of radio transmission. Aircraft in the who receive these transmissions send replies. Information in these replies allow the TCAS system to determine if a nearby aircraft may travel too close to itself. TCAS can then determine help both pilots avoid a mid-air collision. Information in the messages can be faked by a malicious actor. To explore these vulnerabilities a test bed is built with commercial grade TCAS equipment. Several types of attacks are evaluated.
Pelixo, Dário Miguel da Silva. "CPPS-3D: a methodology to support cyber physical production systems design, development and deployment." Master's thesis, Instituto Politécnico de Setúbal. Escola Superior de Tecnologia de Setúbal, 2019. http://hdl.handle.net/10400.26/31368.
Full textCyber-Physical Production Systems are widely recognized as the key to unlock the full potential benefits of the Industry 4.0 paradigm. Cyber-Physical Production Systems Design, Development and Deployment methodology is a systematic approach in assessing necessities, identifying gaps and then designing, developing and deploying solutions to fill such gaps. It aims to support and drive enterprise’s evolution to the new working environment promoted by the availability of Industry 4.0 paradigms and technologies while challenged by the need to increment a continuous improvement culture. The proposed methodology considers the different dimensions within enterprises related with their levels of organization, competencies and technology. It is a two-phased sequentially-stepped process to enable discussion, reflection/reasoning, decision-making and action-taking towards evolution. The first phase assesses an enterprise across its Organizational, Technological and Human dimensions. The second phase establishes sequential tasks to successfully deploy solutions. Is was applied to a production section at a Portuguese enterprise with the development of a new visual management system to enable shop floor management. This development is presented as an example of Industry 4.0 technology and it promotes a faster decision-making, better production management, improved data availability as well as fosters more dynamic workplaces with enhanced reactivity to problems.
Maurer, Simon. "Analysis and coordination of mixed-criticality cyber-physical systems." Thesis, University of Hertfordshire, 2018. http://hdl.handle.net/2299/21094.
Full textKatzenbach, Alfred, and Holger Frielingsdorf. "Big Data Analytics für die Produktentwicklung." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2016. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-214517.
Full textJagtap, Vinayak. "Cyber Physical System for Continuous Evaluation of Fall Risks to Enable Aging-In-Place." Digital WPI, 2015. https://digitalcommons.wpi.edu/etd-theses/508.
Full textGries, Stefan [Verfasser], and Volker [Akademischer Betreuer] Gruhn. "Information Flow Monitoring in Cyber-Physical Systems : Nachvollziehen von Cascading Data Corruption in CPS / Stefan Gries ; Betreuer: Volker Gruhn." Duisburg, 2021. http://d-nb.info/1237221501/34.
Full textTheiss, Sebastian. "Echtzeitfähige Softwareagenten zur Realisierung cyber-physischer Produktionssysteme." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2016. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-211768.
Full textBooks on the topic "Cyber-Physical Systems (CPSs)"
Kagaku Gijutsu Shinkō Kikō. Kenkyū Kaihatsu Senryaku Sentā. Denshi Jōhō Tsūshin Yunitto. CPS (Cyber Physical Systems) kiban gijutsu no kenkyū kaihatsu to sono shakai e no dōnyū ni kansuru teian: Kōreisha no shakai sanka sokushin o jirei to shite = Research and development on fundamental technologies of cyber physical systems and their social implementation : a case study on promoting aged people to social activities. Tōkyō-to Chiyoda-ku: Kagaku Gijutsu Shinkō Kikō Kenkyū Kaihatsu Senryaku Sentā Denshi Jōhō Tsūshin Yunitto, 2013.
Find full textStaff, IEEE. 2022 Workshop on Cyber Physical Systems for Emergency Response (CPS ER). IEEE, 2022.
Find full textStaff, IEEE. 2022 Workshop on Benchmarking Cyber Physical Systems and Internet of Things (CPS IoTBench). IEEE, 2022.
Find full textStaff, IEEE. 2022 2nd International Workshop on Cyber Physical Human System Design and Implementation (CPHS). IEEE, 2022.
Find full textAgrawal, Dharma P., Kuan-Ching Li, and Brij B. Gupta. Recent Advances in Security, Privacy, and Trust for Internet of Things (IoT) and Cyber-Physical Systems (CPS). Taylor & Francis Group, 2020.
Find full textAgrawal, Dharma P., Kuan-Ching Li, and Brij B. Gupta. Recent Advances in Security, Privacy, and Trust for Internet of Things (IoT) and Cyber-Physical Systems (CPS). Taylor & Francis Group, 2020.
Find full textRecent Advances in Security, Privacy, and Trust for Internet of Things (IoT) and Cyber-Physical Systems (CPS). Taylor & Francis Group, 2020.
Find full textAgrawal, Dharma P., Kuan-Ching Li, and Brij B. Gupta. Recent Advances in Security, Privacy, and Trust for Internet of Things (IoT) and Cyber-Physical Systems (CPS). Taylor & Francis Group, 2020.
Find full textAgrawal, Dharma P., Kuan-Ching Li, and Brij Gupta. Recent Advances in Security Privacy and Trust for Internet-Of-things (iot) and Cyber-physical Systems (cps). Taylor & Francis Group, 2020.
Find full textStaff, IEEE. 2022 2nd Workshop on Data Driven and Intelligent Cyber Physical Systems for Smart Cities Workshop (DI CPS). IEEE, 2022.
Find full textBook chapters on the topic "Cyber-Physical Systems (CPSs)"
Wang, Yong, and Jason Nikolai. "Key Management in CPSs." In Security and Privacy in Cyber-Physical Systems, 117–36. Chichester, UK: John Wiley & Sons, Ltd, 2017. http://dx.doi.org/10.1002/9781119226079.ch6.
Full textde la Torre, Eduardo. "Adaptivity and Self-awareness of CPSs and CPSoSs." In Heterogeneous Cyber Physical Systems of Systems, 37–60. New York: River Publishers, 2022. http://dx.doi.org/10.1201/9781003338390-3.
Full textWu, Chengwei, Weiran Yao, Guanghui Sun, and Ligang Wu. "Learning Tracking Control for CPSs." In Security of Cyber-Physical Systems: State Estimation and Control, 61–87. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-88350-8_4.
Full textWu, Chengwei, Weiran Yao, Guanghui Sun, and Ligang Wu. "Proactive Secure Control for CPSs." In Security of Cyber-Physical Systems: State Estimation and Control, 181–213. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-88350-8_9.
Full textWu, Chengwei, Weiran Yao, Guanghui Sun, and Ligang Wu. "Optimal DoS Attack Scheduling for CPSs." In Security of Cyber-Physical Systems: State Estimation and Control, 15–32. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-88350-8_2.
Full textAsavoae, Mihail, Imane Haur, Mathieu Jan, Belgacem Ben Hedia, and Martin Schoeberl. "Towards Formal Co-validation of Hardware and Software Timing Models of CPSs." In Cyber Physical Systems. Model-Based Design, 203–27. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-41131-2_10.
Full textNehinbe, Joshua Ojo. "A Model for Auditing Smart Intrusion Detection Systems (IDSs) and Log Analyzers in Cyber-Physical Systems (CPSs)." In Security in Cyber-Physical Systems, 123–53. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-67361-1_5.
Full textWu, Chengwei, Weiran Yao, Guanghui Sun, and Ligang Wu. "Secure Estimation for CPSs via Sliding Mode." In Security of Cyber-Physical Systems: State Estimation and Control, 135–60. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-88350-8_7.
Full textWu, Chengwei, Weiran Yao, Guanghui Sun, and Ligang Wu. "Active Defense Control of CPSs via Sliding Mode." In Security of Cyber-Physical Systems: State Estimation and Control, 33–60. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-88350-8_3.
Full textZhang, Jinhui, Yuanqing Xia, Zhongqi Sun, and Duanduan Chen. "Observer-Based Event-Triggered Control for CPSs." In Networked and Event-Triggered Control Approaches in Cyber-Physical Systems, 97–110. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781003260882-8.
Full textConference papers on the topic "Cyber-Physical Systems (CPSs)"
Rosen, David W., and Young Mi Choi. "Generative Design of Cyber-Physical-Human System Families: Concepts and Research Issues." In ASME 2022 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2022. http://dx.doi.org/10.1115/detc2022-91265.
Full textvan Beek, Anton. "A Decision-Centric Perspective on Evolving Cyber-Physical-Social Systems: Effectiveness, Group Value, and Opportunities." In ASME 2022 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2022. http://dx.doi.org/10.1115/detc2022-90161.
Full textOpiyo, Eliab Z., and Imre Horváth. "Feature-Based Prognosis of Performance and Cost Implications of Cyber-Physical Systems: An Illustration of Theory and Process." In ASME 2014 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/detc2014-34343.
Full textWang, Yan. "Design of Trustworthy Cyber-Physical-Social Systems With Discrete Bayesian Optimization." In ASME 2020 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/detc2020-22661.
Full textHorváth, Imre, Zoltán Rusák, and Yongzhe Li. "Order Beyond Chaos: Introducing the Notion of Generation to Characterize the Continuously Evolving Implementations of Cyber-Physical Systems." In ASME 2017 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/detc2017-67082.
Full textLukina, Anna. "Resilient Control and Safety for Multi-Agent Cyber-Physical Systems." In Twenty-Sixth International Joint Conference on Artificial Intelligence. California: International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/753.
Full textFazio, Maria, Antonella Longo, Rajiv Ranjan, and Marco Zappatore. "1st Workshop on Cyber-Physical Social Systems (CPSS) 2019." In IoT 2019: 9th International Conference on the Internet of Things. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3365871.3365902.
Full textHorváth, Imre, and Junfeng Wang. "Towards a Comprehensive Theory of Multi-Aspect Interaction With Cyber Physical Systems." In ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/detc2015-47243.
Full textYang, Xiaoou, Ahreum Lim, Aliki Nicolaides, and Beshoy Morkos. "Towards the Understanding of Nudging Strategies in Cyber-Physical-Social System In Manufacturing Environments." In ASME 2022 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2022. http://dx.doi.org/10.1115/detc2022-90863.
Full textGerritsen, Bart H. M., and Imre Horváth. "Current Drivers and Obstacles of Synergy in Cyber-Physical Systems Design." In ASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/detc2012-71156.
Full textReports on the topic "Cyber-Physical Systems (CPSs)"
Ospina Casas, Juan. Towards the Secure Operation of Cyber-Physical Energy Systems (CPES). Office of Scientific and Technical Information (OSTI), October 2022. http://dx.doi.org/10.2172/1894795.
Full textWang, Wenbo, Xin Fang, Hantao Cui, Jinning Wang, Fangxing Li, Yijing Liu, Thomas Overbye, Mengmeng Cai, and Chris Irwin. Cyber-Physical Dynamic System (CPDS) Modeling for Frequency Regulation and AGC Services of Distributed Energy Resources. Office of Scientific and Technical Information (OSTI), August 2022. http://dx.doi.org/10.2172/1882191.
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