{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,30]],"date-time":"2026-03-30T22:31:23Z","timestamp":1774909883186,"version":"3.50.1"},"reference-count":148,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2023,7,8]],"date-time":"2023-07-08T00:00:00Z","timestamp":1688774400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>The smart city vision has driven the rapid development and advancement of interconnected technologies using the Internet of Things (IoT) and cyber-physical systems (CPS). In this paper, various aspects of IoT and CPS in recent years (from 2013 to May 2023) are surveyed. It first begins with industry standards which ensure cost-effective solutions and interoperability. With ever-growing big data, tremendous undiscovered knowledge can be mined to be transformed into useful applications. Machine learning algorithms are taking the lead to achieve various target applications with formulations such as classification, clustering, regression, prediction, and anomaly detection. Notably, attention has shifted from traditional machine learning algorithms to advanced algorithms, including deep learning, transfer learning, and data generation algorithms, to provide more accurate models. In recent years, there has been an increasing need for advanced security techniques and defense strategies to detect and prevent the IoT and CPS from being attacked. Research challenges and future directions are summarized. We hope that more researchers can conduct more studies on the IoT and on CPS.<\/jats:p>","DOI":"10.3390\/info14070388","type":"journal-article","created":{"date-parts":[[2023,7,10]],"date-time":"2023-07-10T00:54:23Z","timestamp":1688950463000},"page":"388","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":45,"title":["A Survey of Internet of Things and Cyber-Physical Systems: Standards, Algorithms, Applications, Security, Challenges, and Future Directions"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7992-9901","authenticated-orcid":false,"given":"Kwok Tai","family":"Chui","sequence":"first","affiliation":[{"name":"Department of Electronic Engineering and Computer Science, School of Science and Technology, Hong Kong Metropolitan University, Hong Kong, China"}]},{"given":"Brij B.","family":"Gupta","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Information Engineering, Asia University, Taichung 41354, Taiwan"},{"name":"Symbiosis Centre for Information Technology (SCIT), Symbiosis International University, Pune 412115, India"},{"name":"Lebanese American University, Beirut 1102, Lebanon"},{"name":"Center for Interdisciplinary Research at University of Petroleum and Energy Studies (UPES), Dehradun 248007, India"},{"name":"School of Computing, Skyline University College, Sharjah P.O. Box 1797, United Arab Emirates"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-0203-3564","authenticated-orcid":false,"given":"Jiaqi","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Electronic Engineering and Computer Science, School of Science and Technology, Hong Kong Metropolitan University, Hong Kong, China"}]},{"given":"Varsha","family":"Arya","sequence":"additional","affiliation":[{"name":"Department of Business Administration, Asia University, Taichung 41354, Taiwan"},{"name":"UCRD, Chandigarh University, Chandigarh 140413, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1656-6397","authenticated-orcid":false,"given":"Nadia","family":"Nedjah","sequence":"additional","affiliation":[{"name":"Department of Electronics Engineering and Telecommunications, Faculty of Engineering, State University of Rio de Janeiro, R. S\u00e3o Francisco Xavier, 524, Maracan\u00e3, Rio de Janeiro 20550-900, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8808-6114","authenticated-orcid":false,"given":"Ammar","family":"Almomani","sequence":"additional","affiliation":[{"name":"School of Computing, Skyline University College, Sharjah P.O. Box 1797, United Arab Emirates"},{"name":"IT-Department, Al-Huson University College, Al-Balqa Applied University, Al-Salt 19117, Jordan"}]},{"given":"Priyanka","family":"Chaurasia","sequence":"additional","affiliation":[{"name":"School of Computing, Ulster University, Londonderry BT48 7JL, UK"}]}],"member":"1968","published-online":{"date-parts":[[2023,7,8]]},"reference":[{"key":"ref_1","first-page":"1","article-title":"Taxonomical challenges for cyber incident response threat intelligence: A review","volume":"12","author":"Ammi","year":"2022","journal-title":"Int. J. Comput. Appl."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"150","DOI":"10.1016\/j.jpdc.2021.03.011","article-title":"Secure blockchain enabled Cyber\u2013physical systems in healthcare using deep belief network with ResNet model","volume":"153","author":"Nguyen","year":"2021","journal-title":"J. Parallel Distrib. Comput."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1","DOI":"10.4018\/IJSSCI.285593","article-title":"Security of cloud-based medical internet of things (miots): A survey","volume":"14","author":"Gaurav","year":"2022","journal-title":"Int. J. Softw. Sci. Comput. Intell."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1","DOI":"10.4018\/IJSWIS.297143","article-title":"Distributed denial-of-service (DDoS) attacks and defense mechanisms in various web-enabled computing platforms: Issues, challenges, and future research directions","volume":"18","author":"Singh","year":"2022","journal-title":"Int. J. Semant. Web Inf. Syst."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"176","DOI":"10.1016\/j.jmsy.2020.11.017","article-title":"Cyber-physical systems architectures for industrial internet of things applications in Industry 4.0: A literature review","volume":"58","author":"Pivoto","year":"2021","journal-title":"J. Manuf. Syst."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"2351","DOI":"10.1109\/COMST.2021.3106669","article-title":"A survey of honeypots and honeynets for internet of things, industrial internet of things, and cyber-physical systems","volume":"23","author":"Franco","year":"2021","journal-title":"IEEE Commun. Surv. Tutor."},{"key":"ref_7","first-page":"1","article-title":"Detecting and preventing misbehaving intruders in the internet of vehicles","volume":"12","author":"Sharma","year":"2022","journal-title":"Int. J. Comput. Appl."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"689590","DOI":"10.3389\/frcmn.2021.689590","article-title":"Smarter grid in the 5G Era: A framework integrating power internet of things with a cyber physical system","volume":"2","author":"Liu","year":"2021","journal-title":"Front. Commun. Netw."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"4671","DOI":"10.1016\/j.matpr.2022.03.123","article-title":"Security and privacy challenges in the deployment of cyber-physical systems in smart city applications: State-of-art work","volume":"62","author":"Rani","year":"2022","journal-title":"Mater. Today Proc."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"6379","DOI":"10.1007\/s12652-021-03656-1","article-title":"Towards a cyber-physical system for sustainable and smart building: A use case for optimizing water consumption on a SmartCampus","volume":"14","author":"Barroso","year":"2023","journal-title":"J. Ambient Intell. Humaniz. Comput."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"111631","DOI":"10.1016\/j.jss.2023.111631","article-title":"A literature review of IoT and CPS\u2014What they are, and what they are not","volume":"200","author":"Lesch","year":"2023","journal-title":"J. Syst. Softw."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"171","DOI":"10.1007\/s41315-021-00180-5","article-title":"Digital twins: Artificial intelligence and the IoT cyber-physical systems in Industry 4.0","volume":"6","author":"Radanliev","year":"2022","journal-title":"Int. J. Intell. Robot. Appl."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"274","DOI":"10.1016\/j.comcom.2021.09.029","article-title":"AI-empowered, blockchain and SDN integrated security architecture for IoT network of cyber physical systems","volume":"181","author":"Latif","year":"2022","journal-title":"Comput. Commun."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1109\/MITP.2019.2912604","article-title":"Cyber physical systems and IoT: Architectural practices, interoperability, and transformation","volume":"22","author":"Fatima","year":"2020","journal-title":"IT Prof."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Kwon, Y., Lee, S., King, R., Lim, J.I., and Kim, H.K. (2019). Behavior analysis and anomaly detection for a digital substation on cyber-physical system. Electronics, 8.","DOI":"10.3390\/electronics8030326"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Gaggero, G.B., Rossi, M., Girdinio, P., and Marchese, M. (2022, January 20\u201322). Cybersecurity Issues in Communication-Based Electrical Protections. Proceedings of the 2022 International Conference on Electrical, Computer and Energy Technologies, Prague, Czech Republic.","DOI":"10.1109\/ICECET55527.2022.9873081"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"7363","DOI":"10.3390\/app11167363","article-title":"Advancements and research trends in microgrids cybersecurity","volume":"11","author":"Gaggero","year":"2021","journal-title":"Appl. Sci."},{"key":"ref_18","unstructured":"Hinkel, G. (2017, January 21). The TTC 2017 Outage System Case for Incremental Model Views. Proceedings of the 10th Transformation Tool Contest, Marburg, Germany."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"100466","DOI":"10.1016\/j.ijcip.2021.100466","article-title":"Threat modelling of cyber\u2013physical systems using an applied \u03c0-calculus","volume":"35","author":"Nweke","year":"2021","journal-title":"Int. J. Crit. Infrastruct. Prot."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Balijepalli, V.M., Sielker, F., and Karmakar, G. (2021, January 18\u201321). Evolution of power system cim to digital twins-a comprehensive review and analysis. Proceedings of the 2021 IEEE PES Innovative Smart Grid Technologies Europe, Espoo, Finland.","DOI":"10.1109\/ISGTEurope52324.2021.9640174"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"3214","DOI":"10.1109\/TSG.2022.3156897","article-title":"LoMoS: Less-online\/more-offline signatures for extremely time-critical systems","volume":"13","author":"Esiner","year":"2022","journal-title":"IEEE Trans. Smart Grid"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"2364","DOI":"10.1109\/TII.2014.2332097","article-title":"Analyzing cyber-physical energy systems: The INSPIRE cosimulation of power and ICT systems using HLA","volume":"10","author":"Georg","year":"2014","journal-title":"IEEE Trans. Ind. Inform."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"186","DOI":"10.1049\/iet-cps.2019.0049","article-title":"Prime: A real-time cyber-physical systems testbed: From wide-area monitoring, protection, and control prototyping to operator training and beyond","volume":"5","author":"Becejac","year":"2020","journal-title":"IET Cyber-Phys. Syst. Theory Appl."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"128","DOI":"10.1016\/j.future.2015.09.026","article-title":"Challenges and research directions for heterogeneous cyber\u2013physical system based on IEC 61850: Vulnerabilities, security requirements, and security architecture","volume":"61","author":"Yoo","year":"2016","journal-title":"Future Gener. Comput. Syst."},{"key":"ref_25","unstructured":"Awadid, A. (2022). Advances in Information and Communication, Proceedings of the 2022 Future of Information and Communication Conference, San Francisco, CA, USA, 3\u20134 March 2022, Springer International Publishing."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"570","DOI":"10.1016\/j.egyr.2022.05.207","article-title":"Cyber\u2013physical testbed for Wide Area Measurement System employing IEC 61850 and IEEE C37. 118 based communication","volume":"8","author":"Chawla","year":"2022","journal-title":"Energy Rep."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Rana, S., Zhu, H., Lee, C.W., Nicol, D.M., and Shin, I. (2012, January 3\u20137). The Not-So-Smart grid: Preliminary work on identifying vulnerabilities in ANSI C12.22. Proceedings of the 2012 IEEE Globecom Workshops, Anaheim, CA, USA.","DOI":"10.1109\/GLOCOMW.2012.6477810"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"103715","DOI":"10.1016\/j.compind.2022.103715","article-title":"Managing cybersecurity risks of cyber-physical systems: The MARISMA-CPS pattern","volume":"142","author":"Rosado","year":"2022","journal-title":"Comput. Ind."},{"key":"ref_29","first-page":"106","article-title":"Using Machine Learning to Work Around the Operational and Cybersecurity Limitations of Legacy Process Sensors","volume":"55","author":"Weiss","year":"2022","journal-title":"Computer"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"2181","DOI":"10.3390\/electronics11142181","article-title":"Understanding Cybersecurity Frameworks and Information Security Standards\u2014A Review and Comprehensive Overview","volume":"11","author":"Taherdoost","year":"2022","journal-title":"Electronics"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"9917","DOI":"10.3390\/s22249917","article-title":"Embedded Sensor Systems in Medical Devices: Requisites and Challenges Ahead","volume":"22","author":"Arandia","year":"2022","journal-title":"Sensors"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"872","DOI":"10.3390\/healthcare11060872","article-title":"Threat Assessment and Risk Analysis (TARA) for Interoperable Medical Devices in the Operating Room Inspired by the Automotive Industry","volume":"11","author":"Puder","year":"2023","journal-title":"Healthcare"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Chen, X., Zhang, Q., Zhang, L., Jia, X., Zheng, P., and Yang, X. (2022, January 25\u201327). Standardization of Financial Blockchain: Technologies, Challenges, and Future. Proceedings of the 2022 IEEE 9th International Conference on Cyber Security and Cloud Computing (CSCloud)\/2022 IEEE 8th International Conference on Edge Computing and Scalable Cloud, Xi\u2019an, China.","DOI":"10.1109\/CSCloud-EdgeCom54986.2022.00015"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"David, A. (2021). Unsettled Topics Concerning Airport Cybersecurity Standards and Regulation, SAE Technical Paper. No. EPR2021020.","DOI":"10.4271\/EPR2021020"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1109\/MC.2022.3218364","article-title":"New IEEE Media Sanitization Specification Enables Circular Economy for Storage","volume":"56","author":"Hands","year":"2023","journal-title":"Computer"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Da Rocha, H., Abrishambaf, R., Pereira, J., and Espirito Santo, A. (2022). Integrating the IEEE 1451 and IEC 61499 standards with the industrial internet reference architecture. Sensors, 22.","DOI":"10.3390\/s22041495"},{"key":"ref_37","unstructured":"Rajendran, T., Surya, S., and Babu, N. (2023). New Approaches to Data Analytics and Internet of Things Through Digital Twin, IGI Global."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1109\/MCE.2020.2988441","article-title":"Toward the internet of underwater things: Recent developments and future challenges","volume":"10","author":"Khalil","year":"2020","journal-title":"IEEE Consum. Electron. Mag."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"100420","DOI":"10.1016\/j.iot.2021.100420","article-title":"The challenges of IoT addressing security, ethics, privacy, and laws","volume":"15","author":"Karale","year":"2021","journal-title":"Internet Things"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"164720","DOI":"10.1109\/ACCESS.2021.3135432","article-title":"Toward industrial IoT: Integrated architecture of an OPC UA synergy platform","volume":"9","author":"Lee","year":"2021","journal-title":"IEEE Access"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"24920","DOI":"10.1109\/JSEN.2021.3055618","article-title":"Artificial intelligence-based sensors for next generation IoT applications: A review","volume":"21","author":"Mukhopadhyay","year":"2021","journal-title":"IEEE Sens. J."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Shang, K., McDonald, S., Buticchi, G., and Brusic, V. (July, January 27). The development of ethically informed standards for intelligent monitoring systems of electric machines. Proceedings of the 2022 IEEE 46th Annual Computers, Software, and Applications Conference, Los Alamitos, CA, USA.","DOI":"10.1109\/COMPSAC54236.2022.00254"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"103632","DOI":"10.1016\/j.compind.2022.103632","article-title":"A generic interface and a framework designed for industrial metrology integration for the Internet of Things","volume":"138","author":"Sousa","year":"2022","journal-title":"Comput. Ind."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"741","DOI":"10.3390\/iot2040037","article-title":"Facilitating Semantic Interoperability of Trustworthy IoT Entities in Cultural Spaces: The Smart Museum Ontology","volume":"2","author":"Zachila","year":"2021","journal-title":"IoT"},{"key":"ref_45","first-page":"9641143","article-title":"The Development of Privacy Protection Standards for Smart Home","volume":"2022","author":"Liu","year":"2022","journal-title":"Wirel. Commun. Mob. Comput."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"104536","DOI":"10.1016\/j.jmva.2019.104536","article-title":"Classification with many classes: Challenges and pluses","volume":"174","author":"Abramovich","year":"2019","journal-title":"J. Multivar. Anal."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"102526","DOI":"10.1016\/j.jnca.2019.102526","article-title":"The rise of machine learning for detection and classification of malware: Research developments, trends and challenges","volume":"153","author":"Gibert","year":"2020","journal-title":"J. Netw. Comput. Appl."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"2552","DOI":"10.3390\/math10152552","article-title":"Review of Artificial Intelligence and Machine Learning Technologies: Classification, Restrictions, Opportunities and Challenges","volume":"10","author":"Mukhamediev","year":"2022","journal-title":"Mathematics"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"e00938","DOI":"10.1016\/j.heliyon.2018.e00938","article-title":"State-of-the-art in artificial neural network applications: A survey","volume":"4","author":"Abiodun","year":"2018","journal-title":"Heliyon"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"7657","DOI":"10.1007\/s00500-021-05732-2","article-title":"A biometric cryptosystem scheme based on random projection and neural network","volume":"25","author":"Peng","year":"2021","journal-title":"Soft Comput."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"1915","DOI":"10.3390\/electronics12081915","article-title":"A Convolutional Neural Network-Based Feature Extraction and Weighted Twin Support Vector Machine Algorithm for Context-Aware Human Activity Recognition","volume":"12","author":"Chui","year":"2023","journal-title":"Electronics"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"1","DOI":"10.4018\/IJSSCI.312562","article-title":"Analysis of Protein Structure for Drug Repurposing Using Computational Intelligence and ML Algorithm","volume":"14","author":"Srivastava","year":"2022","journal-title":"Int. J. Softw. Sci. Comput. Intell."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"643","DOI":"10.1002\/joom.1228","article-title":"Supervised machine learning for theory building and testing: Opportunities in operations management","volume":"2023","author":"Chou","year":"2023","journal-title":"J. Oper. Manag."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"1","DOI":"10.4018\/IJSWIS.297032","article-title":"Phishing website detection with semantic features based on machine learning classifiers: A comparative study","volume":"18","author":"Almomani","year":"2022","journal-title":"Int. J. Semant. Web Inf. Syst."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"164","DOI":"10.1016\/j.ins.2023.02.088","article-title":"A review on semi-supervised clustering","volume":"632","author":"Cai","year":"2023","journal-title":"Inf. Sci."},{"key":"ref_56","first-page":"100668","article-title":"Driver stress recognition for smart transportation: Applying multiobjective genetic algorithm for improving fuzzy c-means clustering with reduced time and model complexity","volume":"35","author":"Chui","year":"2022","journal-title":"Sustain. Comput. Inform. Syst."},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Chui, K.T., Tsang, K.F., Chung, S.H., and Yeung, L.F. (2013, January 10\u201313). Appliance signature identification solution using K-means clustering. Proceedings of the IECON 2013-39th Annual Conference of the IEEE Industrial Electronics Society, Vienna, Austria.","DOI":"10.1109\/IECON.2013.6700545"},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"178","DOI":"10.1016\/j.ins.2022.11.139","article-title":"K-means Clustering Algorithms: A Comprehensive Review, Variants Analysis, and Advances in the Era of Big Data","volume":"622","author":"Ikotun","year":"2023","journal-title":"Inf. Sci."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"128","DOI":"10.1016\/j.jpdc.2019.07.015","article-title":"A distributed approximate nearest neighbors algorithm for efficient large scale mean shift clustering","volume":"134","author":"Beck","year":"2019","journal-title":"J. Parallel Distrib. Comput."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"107086","DOI":"10.1016\/j.measurement.2019.107086","article-title":"Automated liver and tumor segmentation based on concave and convex points using fuzzy c-means and mean shift clustering","volume":"150","author":"Ranjbarzadeh","year":"2020","journal-title":"Measurement"},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"2223","DOI":"10.1109\/TPAMI.2013.28","article-title":"Multi-exemplar affinity propagation","volume":"35","author":"Wang","year":"2013","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_62","doi-asserted-by":"crossref","unstructured":"Rahman, M.R., Arefin, M.S., Rahman, S., Ahmed, A., Islam, T., Dhar, P.K., and Kwon, O.J. (2022). A Comprehensive Survey on Affinity Analysis, Bibliomining, and Technology Mining: Past, Present, and Future Research. Appl. Sci., 12.","DOI":"10.3390\/app12105227"},{"key":"ref_63","doi-asserted-by":"crossref","unstructured":"Pento\u015b, K., Mbah, J.T., Pieczarka, K., Niedba\u0142a, G., and Wojciechowski, T. (2022). Evaluation of multiple linear regression and machine learning approaches to predict soil compaction and shear stress based on electrical parameters. Appl. Sci., 12.","DOI":"10.3390\/app12178791"},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"636","DOI":"10.1111\/2041-210X.12577","article-title":"A protocol for conducting and presenting results of regression-type analyses","volume":"7","author":"Zuur","year":"2016","journal-title":"Methods Ecol. Evol."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/j.neunet.2018.12.010","article-title":"An extensive experimental survey of regression methods","volume":"111","author":"Sirsat","year":"2019","journal-title":"Neural Netw."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1016\/j.future.2023.02.022","article-title":"A privacy-preserving logistic regression-based diagnosis scheme for digital healthcare","volume":"144","author":"Zhou","year":"2023","journal-title":"Future Gener. Comput. Syst."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1016\/j.jclinepi.2019.02.004","article-title":"A systematic review shows no performance benefit of machine learning over logistic regression for clinical prediction models","volume":"110","author":"Christodoulou","year":"2019","journal-title":"J. Clin. Epidemiol."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"S574","DOI":"10.21037\/jtd.2019.01.25","article-title":"Developing prediction models for clinical use using logistic regression: An overview","volume":"11","author":"Shipe","year":"2019","journal-title":"J. Thorac. Dis."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"e1492","DOI":"10.1002\/wics.1492","article-title":"Robust nonparametric regression: A review","volume":"12","year":"2020","journal-title":"Wiley Interdiscip. Rev. Comput. Stat."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"353","DOI":"10.1038\/s41467-020-20655-6","article-title":"Deep learning encodes robust discriminative neuroimaging representations to outperform standard machine learning","volume":"12","author":"Abrol","year":"2021","journal-title":"Nat. Commun."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"685","DOI":"10.1007\/s12525-021-00475-2","article-title":"Machine learning and deep learning","volume":"31","author":"Janiesch","year":"2021","journal-title":"Electron. Mark."},{"key":"ref_72","doi-asserted-by":"crossref","unstructured":"Lakshmanna, K., Kaluri, R., Gundluru, N., Alzamil, Z.S., Rajput, D.S., Khan, A.A., Haq, M.A., and Alhussen, A. (2022). A review on deep learning techniques for IoT data. Electronics, 11.","DOI":"10.3390\/electronics11101604"},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1016\/j.neucom.2022.06.111","article-title":"Activation functions in deep learning: A comprehensive survey and benchmark","volume":"503","author":"Dubey","year":"2022","journal-title":"Neurocomputing"},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1016\/j.patrec.2023.02.026","article-title":"A deep learning-based fast fake news detection model for cyber-physical social services","volume":"168","author":"Zhang","year":"2023","journal-title":"Pattern Recognit. Lett."},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"151","DOI":"10.1109\/TAI.2021.3054609","article-title":"A decade survey of transfer learning (2010\u20132020)","volume":"1","author":"Niu","year":"2020","journal-title":"IEEE Trans. Artif. Intell."},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"2871","DOI":"10.1007\/s10462-022-10230-4","article-title":"A survey of transfer learning for machinery diagnostics and prognostics","volume":"56","author":"Yao","year":"2023","journal-title":"Artif. Intell. Rev."},{"key":"ref_77","first-page":"1","article-title":"Applications of unsupervised deep transfer learning to intelligent fault diagnosis: A survey and comparative study","volume":"70","author":"Zhao","year":"2021","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref_78","doi-asserted-by":"crossref","unstructured":"Luo, Y., Zhang, Z., Zhang, L., Han, J., Cao, J., and Zhang, J. (2022). Developing High-Resolution Crop Maps for Major Crops in the European Union Based on Transductive Transfer Learning and Limited Ground Data. Remote Sens., 14.","DOI":"10.3390\/rs14081809"},{"key":"ref_79","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Xia, K., Jiang, Y., Qian, P., Cai, W., Qiu, C., Wee, L.K., and Wu, D. (2022). Multi-modality fusion & inductive knowledge transfer underlying non-sparse multi-kernel learning and distribution adaption. IEEE ACM Trans. Comput. Biol. Bioinform.","DOI":"10.1109\/TCBB.2022.3142748"},{"key":"ref_80","first-page":"1","article-title":"Two-stage cross-modality transfer learning method for military-civilian SAR ship recognition","volume":"19","author":"Song","year":"2022","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"102468","DOI":"10.1016\/j.rcim.2022.102468","article-title":"Multiple source partial knowledge transfer for manufacturing system modelling","volume":"80","author":"Liu","year":"2023","journal-title":"Robot. Comput. Integr. Manuf."},{"key":"ref_82","doi-asserted-by":"crossref","first-page":"6376275","DOI":"10.1155\/2023\/6376275","article-title":"Multiround transfer learning and modified generative adversarial network for lung cancer detection","volume":"2023","author":"Chui","year":"2023","journal-title":"Int. J. Intell. Syst."},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1016\/j.inffus.2022.07.025","article-title":"Partial feedback online transfer learning with multi-source domains","volume":"89","author":"Kang","year":"2023","journal-title":"Inf. Fus."},{"key":"ref_84","doi-asserted-by":"crossref","first-page":"110345","DOI":"10.1016\/j.knosys.2023.110345","article-title":"Attention-based deep meta-transfer learning for few-shot fine-grained fault diagnosis","volume":"264","author":"Li","year":"2023","journal-title":"Knowl.-Based Syst."},{"key":"ref_85","doi-asserted-by":"crossref","unstructured":"Qian, Q., Zhou, J., and Qin, Y. (2023). Relationship Transfer Domain Generalization Network for Rotating Machinery Fault Diagnosis Under Different Working Conditions. IEEE Trans. Ind. Inform.","DOI":"10.1109\/TII.2022.3232842"},{"key":"ref_86","doi-asserted-by":"crossref","first-page":"1601","DOI":"10.1016\/S0140-6736(22)00232-X","article-title":"Synthetic patient data in health care: A widening legal loophole","volume":"399","author":"Arora","year":"2022","journal-title":"Lancet"},{"key":"ref_87","doi-asserted-by":"crossref","unstructured":"Matuzevi\u010dius, D. (2022). Synthetic Data Generation for the Development of 2D Gel Electrophoresis Protein Spot Models. Appl. Sci., 12.","DOI":"10.3390\/app12094393"},{"key":"ref_88","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s40537-019-0197-0","article-title":"A survey on image data augmentation for deep learning","volume":"6","author":"Shorten","year":"2019","journal-title":"J. Big Data"},{"key":"ref_89","doi-asserted-by":"crossref","first-page":"545","DOI":"10.1111\/1754-9485.13261","article-title":"A review of medical image data augmentation techniques for deep learning applications","volume":"65","author":"Chlap","year":"2021","journal-title":"J. Med. Imaging Radiat. Oncol."},{"key":"ref_90","doi-asserted-by":"crossref","first-page":"109347","DOI":"10.1016\/j.patcog.2023.109347","article-title":"A comprehensive survey of image augmentation techniques for deep learning","volume":"137","author":"Xu","year":"2023","journal-title":"Pattern Recognit."},{"key":"ref_91","doi-asserted-by":"crossref","first-page":"973","DOI":"10.1007\/s10639-022-11177-3","article-title":"Interacting with educational chatbots: A systematic review","volume":"28","author":"Kuhail","year":"2023","journal-title":"Educ. Inf. Technol."},{"key":"ref_92","doi-asserted-by":"crossref","unstructured":"Lin, C.C., Huang, A.Y., and Yang, S.J. (2023). A review of ai-driven conversational chatbots implementation methodologies and challenges (1999\u20132022). Sustainability, 15.","DOI":"10.3390\/su15054012"},{"key":"ref_93","doi-asserted-by":"crossref","unstructured":"Singh, A., and Ogunfunmi, T. (2022). An overview of variational autoencoders for source separation, finance, and bio-signal applications. Entropy, 24.","DOI":"10.3390\/e24010055"},{"key":"ref_94","doi-asserted-by":"crossref","unstructured":"Figueira, A., and Vaz, B. (2022). Survey on synthetic data generation, evaluation methods and GANs. Mathematics, 10.","DOI":"10.3390\/math10152733"},{"key":"ref_95","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3559540","article-title":"Generative adversarial networks in time series: A systematic literature review","volume":"55","author":"Brophy","year":"2023","journal-title":"ACM Comput. Surv."},{"key":"ref_96","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3527849","article-title":"The Role of generative adversarial network in medical image analysis: An in-depth survey","volume":"55","author":"AlAmir","year":"2022","journal-title":"ACM Comput. Surv."},{"key":"ref_97","doi-asserted-by":"crossref","unstructured":"Su\u00e1rez, P.L., Sappa, A.D., and Vintimilla, B.X. (2017, January 21\u201326). Infrared image colorization based on a triplet dcgan architecture. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, Honolulu, HI, USA.","DOI":"10.1109\/CVPRW.2017.32"},{"key":"ref_98","unstructured":"Mirza, M., and Osindero, S. (2014). Conditional generative adversarial nets. arXiv."},{"key":"ref_99","unstructured":"Chen, X., Duan, Y., Houthooft, R., Schulman, J., Sutskever, I., and Abbeel, P. (2016, January 5\u201310). Infogan: Interpretable representation learning by information maximizing generative adversarial nets. Proceedings of the Annual Conference on Neural Information Processing Systems 2016, Barcelona, Spain."},{"key":"ref_100","unstructured":"Odena, A., Olah, C., and Shlens, J. (2017, January 6\u201311). Conditional image synthesis with auxiliary classifier gans. Proceedings of the International Conference on Machine Learning, Sydney, Australia."},{"key":"ref_101","unstructured":"Donahue, J., Kr\u00e4henb\u00fchl, P., and Darrell, T. (2016). Adversarial feature learning. arXiv."},{"key":"ref_102","doi-asserted-by":"crossref","first-page":"1118","DOI":"10.1007\/s11263-019-01265-2","article-title":"Loss-sensitive generative adversarial networks on lipschitz densities","volume":"128","author":"Qi","year":"2020","journal-title":"Int. J. Comput. Vis."},{"key":"ref_103","doi-asserted-by":"crossref","first-page":"3094","DOI":"10.1109\/JIOT.2021.3112159","article-title":"Intelligent intrusion detection for internet of things security: A deep convolutional generative adversarial network-enabled approach","volume":"10","author":"Wu","year":"2023","journal-title":"IEEE Int. Things J."},{"key":"ref_104","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3404890","article-title":"Blockchain-enabled tensor-based conditional deep convolutional GAN for Cyber-physical-Social systems","volume":"21","author":"Feng","year":"2021","journal-title":"ACM Trans. Internet Technol."},{"key":"ref_105","doi-asserted-by":"crossref","unstructured":"Le, K.H., Nguyen, M.H., Tran, T.D., and Tran, N.D. (2022). IMIDS: An intelligent intrusion detection system against cyber threats in IoT. Electronics, 11.","DOI":"10.3390\/electronics11040524"},{"key":"ref_106","doi-asserted-by":"crossref","first-page":"e328","DOI":"10.7717\/peerj-cs.328","article-title":"Data augmentation-based conditional Wasserstein generative adversarial network-gradient penalty for XSS attack detection system","volume":"6","author":"Mokbal","year":"2020","journal-title":"PeerJ Comput. Sci."},{"key":"ref_107","doi-asserted-by":"crossref","first-page":"13725","DOI":"10.1007\/s11042-019-08600-2","article-title":"An analysis of generative adversarial networks and variants for image synthesis on MNIST dataset","volume":"79","author":"Cheng","year":"2020","journal-title":"Multimed. Tools Appl."},{"key":"ref_108","doi-asserted-by":"crossref","first-page":"106467","DOI":"10.1016\/j.knosys.2020.106467","article-title":"Comparative study on the time series forecasting of web traffic based on statistical model and Generative Adversarial model","volume":"213","author":"Zhou","year":"2021","journal-title":"Knowl.-Based Syst."},{"key":"ref_109","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3540198","article-title":"CAN bus intrusion detection based on auxiliary classifier GAN and out-of-distribution detection","volume":"21","author":"Zhao","year":"2022","journal-title":"ACM Trans. Embed. Comput. Syst."},{"key":"ref_110","doi-asserted-by":"crossref","first-page":"4068","DOI":"10.1109\/TDSC.2021.3118636","article-title":"Generative-adversarial class-imbalance learning for classifying cyber-attacks and faults-a cyber-physical power system","volume":"19","author":"Hallaji","year":"2022","journal-title":"IEEE Trans. Dependable Secure Comput."},{"key":"ref_111","doi-asserted-by":"crossref","unstructured":"Xu, W., Jang-Jaccard, J., Liu, T., Sabrina, F., and Kwak, J. (2022). Improved Bidirectional GAN-Based Approach for Network Intrusion Detection Using One-Class Classifier. Computers, 11.","DOI":"10.3390\/computers11060085"},{"key":"ref_112","doi-asserted-by":"crossref","unstructured":"Liao, J., Teo, S.G., Kundu, P.P., and Truong-Huu, T. (2021, January 26\u201328). ENAD: An ensemble framework for unsupervised network anomaly detection. Proceedings of the 2021 IEEE International Conference on Cyber Security and Resilience, Rhodes, Greece.","DOI":"10.1109\/CSR51186.2021.9527982"},{"key":"ref_113","doi-asserted-by":"crossref","first-page":"230","DOI":"10.1016\/j.neucom.2019.05.080","article-title":"Defective samples simulation through adversarial training for automatic surface inspection","volume":"360","author":"Liu","year":"2019","journal-title":"Neurocomputing"},{"key":"ref_114","doi-asserted-by":"crossref","unstructured":"Chen, J., Wang, W.H., Gao, H., and Shi, X. (2021, January 14\u201318). PAR-GAN: Improving the generalization of generative adversarial networks against membership inference attacks. Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining, Singapore.","DOI":"10.1145\/3447548.3467445"},{"key":"ref_115","doi-asserted-by":"crossref","first-page":"102891","DOI":"10.1016\/j.sysarc.2023.102891","article-title":"Towards a real-time IoT: Approaches for incoming packet processing in cyber-physical systems","volume":"140","author":"Behnke","year":"2023","journal-title":"J. Syst. Archit."},{"key":"ref_116","doi-asserted-by":"crossref","first-page":"100766","DOI":"10.1016\/j.iot.2023.100766","article-title":"Threat modeling in smart firefighting systems: Aligning MITRE ATT&CK matrix and NIST security controls","volume":"22","author":"Zahid","year":"2023","journal-title":"Internet Things"},{"key":"ref_117","doi-asserted-by":"crossref","first-page":"e6510","DOI":"10.1002\/cpe.6510","article-title":"Lightweight privacy-aware secure authentication scheme for cyber-physical systems in the edge intelligence era","volume":"35","year":"2023","journal-title":"Concurr. Comput. Pract. Exp."},{"key":"ref_118","doi-asserted-by":"crossref","first-page":"103210","DOI":"10.1016\/j.cose.2023.103210","article-title":"CPS-GUARD: Intrusion detection for cyber-physical systems and IoT devices using outlier-aware deep autoencoders","volume":"129","author":"Catillo","year":"2023","journal-title":"Comput. Secur."},{"key":"ref_119","doi-asserted-by":"crossref","unstructured":"Cicceri, G., Tricomi, G., D\u2019Agati, L., Longo, F., Merlino, G., and Puliafito, A. (2023). A Deep Learning-Driven Self-Conscious Distributed Cyber-Physical System for Renewable Energy Communities. Sensors, 23.","DOI":"10.3390\/s23094549"},{"key":"ref_120","doi-asserted-by":"crossref","first-page":"108651","DOI":"10.1016\/j.compeleceng.2023.108651","article-title":"Federated deep learning for anomaly detection in the internet of things","volume":"108","author":"Wang","year":"2023","journal-title":"Comput. Electr. Eng."},{"key":"ref_121","doi-asserted-by":"crossref","first-page":"108676","DOI":"10.1016\/j.compeleceng.2023.108676","article-title":"Swarm intelligence for IoT attack detection in fog-enabled cyber-physical system","volume":"108","author":"Alohali","year":"2023","journal-title":"Comput. Electr. Eng."},{"key":"ref_122","doi-asserted-by":"crossref","first-page":"108689","DOI":"10.1016\/j.compeleceng.2023.108689","article-title":"Optimal feature selection for malware detection in cyber physical systems using graph convolutional network","volume":"108","author":"Daniel","year":"2023","journal-title":"Comput. Electr. Eng."},{"key":"ref_123","doi-asserted-by":"crossref","first-page":"103174","DOI":"10.1016\/j.cose.2023.103174","article-title":"Attack Path Detection for IIoT Enabled Cyber Physical Systems: Revisited","volume":"128","author":"Arat","year":"2023","journal-title":"Comput. Secur."},{"key":"ref_124","doi-asserted-by":"crossref","first-page":"103167","DOI":"10.1016\/j.cose.2023.103167","article-title":"Network anomaly detection methods in IoT environments via deep learning: A Fair comparison of performance and robustness","volume":"128","author":"Bovenzi","year":"2023","journal-title":"Comput. Secur."},{"key":"ref_125","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1016\/j.aej.2023.02.043","article-title":"Optimization of blasting parameters and prediction of vibration effects in open pit mines based on deep neural networks","volume":"70","author":"Bai","year":"2023","journal-title":"Alex. Eng. J."},{"key":"ref_126","doi-asserted-by":"crossref","first-page":"105838","DOI":"10.1016\/j.engappai.2023.105838","article-title":"Contrastive blind denoising autoencoder for real time denoising of industrial IoT sensor data","volume":"120","author":"Langarica","year":"2023","journal-title":"Eng. Appl. Artif. Intell."},{"key":"ref_127","doi-asserted-by":"crossref","first-page":"2069","DOI":"10.1109\/TMC.2021.3119919","article-title":"Detecting Engine Anomalies Using Batteries","volume":"22","author":"Wang","year":"2023","journal-title":"IEEE Trans. Mob. Comput."},{"key":"ref_128","doi-asserted-by":"crossref","unstructured":"Sadek, R.A., and Elbadawy, H.M. (December, January 29). Towards IoT Era with current and Future Wireless Communication Technologies: An Overview. Proceedings of the 2022 39th National Radio Science Conference, Cairo, Egypt.","DOI":"10.1109\/NRSC57219.2022.9971196"},{"key":"ref_129","doi-asserted-by":"crossref","unstructured":"Monzon Baeza, V., Ortiz, F., Herrero Garcia, S., and Lagunas, E. (2022). Enhanced communications on satellite-based iot systems to support maritime transportation services. Sensors, 22.","DOI":"10.20944\/preprints202208.0320.v1"},{"key":"ref_130","doi-asserted-by":"crossref","unstructured":"Fort, A., Mugnaini, M., Peruzzi, G., and Pozzebon, A. (2022, January 24). Reliability Analysis of an IoT Satellite Facility for Remote Monitoring and Asset Tracking within Marine Environments. Proceedings of the 2022 IEEE International Workshop on Metrology for the Sea; Learning to Measure Sea Health Parameters, Milazzo, Italy.","DOI":"10.1109\/MetroSea55331.2022.9950856"},{"key":"ref_131","doi-asserted-by":"crossref","first-page":"486","DOI":"10.1057\/s41284-021-00286-2","article-title":"Working from home during COVID-19 crisis: A cyber security culture assessment survey","volume":"35","author":"Georgiadou","year":"2022","journal-title":"Secur. J."},{"key":"ref_132","doi-asserted-by":"crossref","first-page":"656","DOI":"10.1016\/j.procs.2021.12.302","article-title":"Overview of social engineering attacks on social networks","volume":"198","author":"Chetioui","year":"2022","journal-title":"Procedia Comput. Sci."},{"key":"ref_133","unstructured":"Ponemon Institute (2020). Cost of Data Breach Report (2020), Ponemon Institute."},{"key":"ref_134","first-page":"13","article-title":"Contract design for the fourth party logistics considering tardiness risk","volume":"13","author":"Wang","year":"2022","journal-title":"Int. J. Ind. Eng. Comput."},{"key":"ref_135","doi-asserted-by":"crossref","first-page":"224677","DOI":"10.1109\/ACCESS.2020.3045322","article-title":"On identifying threats and quantifying cybersecurity risks of mnos deploying heterogeneous rats","volume":"8","author":"Angelogianni","year":"2020","journal-title":"IEEE Access"},{"key":"ref_136","doi-asserted-by":"crossref","first-page":"101731","DOI":"10.1016\/j.cose.2020.101731","article-title":"Holistic cyber hygiene education: Accounting for the human factors","volume":"92","author":"Neigel","year":"2020","journal-title":"Comput. Secur."},{"key":"ref_137","first-page":"379","article-title":"Cloud Computing Security for Multi-Cloud Service Providers: Controls and Techniques in our Modern Threat Landscape","volume":"16","author":"Achar","year":"2022","journal-title":"Int. J. Comput. Syst. Eng."},{"key":"ref_138","doi-asserted-by":"crossref","first-page":"120331","DOI":"10.1109\/ACCESS.2020.3006358","article-title":"Security analysis of IoT devices by using mobile computing: A systematic literature review","volume":"8","author":"Liao","year":"2020","journal-title":"IEEE Access"},{"key":"ref_139","doi-asserted-by":"crossref","first-page":"e4643","DOI":"10.1002\/dac.4643","article-title":"Application of information communication network security management and control based on big data technology","volume":"35","author":"Du","year":"2022","journal-title":"Int. J. Commun. Syst."},{"key":"ref_140","doi-asserted-by":"crossref","unstructured":"Sheikh, A. (2021). Certified Ethical Hacker (CEH) Preparation Guide: Lesson-Based Review of Ethical Hacking and Penetration Testing, Apress.","DOI":"10.1007\/978-1-4842-7258-9"},{"key":"ref_141","doi-asserted-by":"crossref","unstructured":"Tundis, A., Mazurczyk, W., and M\u00fchlh\u00e4user, M. (2018, January 27\u201330). A review of network vulnerabilities scanning tools: Types, capabilities and functioning. Proceedings of the 13th International Conference on Availability, Reliability and Security, Hamburg, Germany.","DOI":"10.1145\/3230833.3233287"},{"key":"ref_142","doi-asserted-by":"crossref","unstructured":"Garba, F.A., Kunya, K.I., Ibrahim, S.A., Isa, A.B., Muhammad, K.M., and Wali, N.N. (2019, January 14\u201317). Evaluating the state of the art antivirus evasion tools on windows and android platform. Proceedings of the 2019 2nd International Conference of the IEEE Nigeria Computer Chapter, Zaria, Nigeria.","DOI":"10.1109\/NigeriaComputConf45974.2019.8949637"},{"key":"ref_143","doi-asserted-by":"crossref","first-page":"1877","DOI":"10.1109\/JAS.2021.1004003","article-title":"Blockchain-assisted secure fine-grained searchable encryption for a cloud-based healthcare cyber-physical system","volume":"8","author":"Gupta","year":"2021","journal-title":"IEEE CAA J. Autom. Sin."},{"key":"ref_144","doi-asserted-by":"crossref","unstructured":"Anwar, R.W., Abdullah, T., and Pastore, F. (2021). Firewall best practices for securing smart healthcare environment: A review. Appl. Sci., 11.","DOI":"10.3390\/app11199183"},{"key":"ref_145","doi-asserted-by":"crossref","first-page":"101657","DOI":"10.1016\/j.giq.2021.101657","article-title":"Enhancing the usability and usefulness of open government data: A comprehensive review of the state of open government data visualization research","volume":"39","author":"Ansari","year":"2022","journal-title":"Gov. Inf. Q."},{"key":"ref_146","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3511102","article-title":"The open data canvas\u2013Analyzing value creation from open data","volume":"3","author":"Gao","year":"2022","journal-title":"Digit. Gov. Res. Prac."},{"key":"ref_147","doi-asserted-by":"crossref","unstructured":"Kamariotou, M., and Kitsios, F. (2022). Bringing Digital Innovation Strategies and Entrepreneurship: The Business Model Canvas in Open Data Ecosystem and Startups. Future Internet, 14.","DOI":"10.3390\/fi14050127"},{"key":"ref_148","doi-asserted-by":"crossref","first-page":"1199","DOI":"10.1109\/COMST.2023.3239579","article-title":"Offloading using traditional optimization and machine learning in federated cloud-edge-fog systems: A survey","volume":"25","author":"Kar","year":"2023","journal-title":"IEEE Commun. Surv. Tutor."}],"container-title":["Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2078-2489\/14\/7\/388\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T20:09:17Z","timestamp":1760126957000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2078-2489\/14\/7\/388"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,7,8]]},"references-count":148,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2023,7]]}},"alternative-id":["info14070388"],"URL":"https:\/\/doi.org\/10.3390\/info14070388","relation":{},"ISSN":["2078-2489"],"issn-type":[{"value":"2078-2489","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,7,8]]}}}