{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,17]],"date-time":"2026-07-17T11:35:19Z","timestamp":1784288119353,"version":"3.55.0"},"reference-count":104,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2025,6,25]],"date-time":"2025-06-25T00:00:00Z","timestamp":1750809600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Future Internet"],"abstract":"<jats:p>As cyber systems increasingly converge with physical infrastructure and social processes, they give rise to Complex Cyber\u2013Physical\u2013Social Systems (C-CPSS), whose emergent behaviors pose unique risks to security and mission assurance. Traditional cyber\u2013physical system models often fail to address the unpredictability arising from human and organizational dynamics, leaving critical gaps in how cyber risks are assessed and managed across interconnected domains. The challenge lies in building resilient systems that not only resist disruption, but also absorb, recover, and adapt\u2014especially in the face of complex, nonlinear, and often unintentionally emergent threats. This paper introduces the concept of \u2018responsible resilience\u2019, defined as the capacity of systems to adapt to cyber risks using trustworthy, transparent agent-based models that operate within socio-technical contexts. We identify a fundamental research gap in the treatment of social complexity and emergence in existing the cyber\u2013physical system literature. To address this, we propose the E3R modeling paradigm\u2014a novel framework for conceptualizing Emergent, Risk-Relevant Resilience in C-CPSS. This paradigm synthesizes human-in-the-loop diagrams, agent-based Artificial Intelligence simulations, and ontology-driven representations to model the interdependencies and feedback loops driving unpredictable cyber risk propagation more effectively. Compared to conventional cyber\u2013physical system models, E3R accounts for adaptive risks across social, cyber, and physical layers, enabling a more accurate and ethically grounded foundation for cyber defence and mission assurance. Our analysis of the literature review reveals the underrepresentation of socio-emergent risk modeling in the literature, and our results indicate that existing models\u2014especially those in industrial and healthcare applications of cyber\u2013physical systems\u2014lack the generalizability and robustness necessary for complex, cross-domain environments. The E3R framework thus marks a significant step forward in understanding and mitigating emergent threats in future digital ecosystems.<\/jats:p>","DOI":"10.3390\/fi17070282","type":"journal-article","created":{"date-parts":[[2025,6,26]],"date-time":"2025-06-26T03:39:59Z","timestamp":1750909199000},"page":"282","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Responsible Resilience in Cyber\u2013Physical\u2013Social Systems: A New Paradigm for Emergent Cyber Risk Modeling"],"prefix":"10.3390","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9373-2179","authenticated-orcid":false,"given":"Theresa","family":"Sobb","sequence":"first","affiliation":[{"name":"School of Systems and Computing, University of New South Wales, Canberra, ACT 2612, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6127-9349","authenticated-orcid":false,"given":"Nour","family":"Moustafa","sequence":"additional","affiliation":[{"name":"School of Systems and Computing, University of New South Wales, Canberra, ACT 2612, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0440-5032","authenticated-orcid":false,"given":"Benjamin","family":"Turnbull","sequence":"additional","affiliation":[{"name":"School of Systems and Computing, University of New South Wales, Canberra, ACT 2612, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,6,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"13559","DOI":"10.48084\/etasr.6969","article-title":"Advancing IoT Cybersecurity: Adaptive threat identification with deep learning in Cyber-physical systems","volume":"14","author":"Atheeq","year":"2024","journal-title":"Eng. Technol. Appl. Sci. Res."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1731","DOI":"10.1007\/s10796-022-10252-x","article-title":"Cyber-physical systems in the context of industry 4.0: A review, categorization and outlook","volume":"26","author":"Oks","year":"2024","journal-title":"Inf. Syst. Front."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"3330","DOI":"10.55248\/gengpi.6.0125.0514","article-title":"Resilient systems: Building secure cyber-physical infrastructure for critical industries against emerging threats","volume":"6","author":"Qudus","year":"2025","journal-title":"Int. J. Res. Publ. Rev."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Kumar, S., and Bhowmik, B. (2024, January 11\u201312). Emergence, evolution, and applications of cyber-physical systems in smart society. Proceedings of the 2024 Fourth International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT), Bhilai, India.","DOI":"10.1109\/ICAECT60202.2024.10468864"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"100938","DOI":"10.1016\/j.arcontrol.2024.100938","article-title":"A real-time interactive decision-making and control framework for complex cyber-physical-human systems","volume":"57","author":"Hu","year":"2024","journal-title":"Annu. Rev. Control"},{"key":"ref_6","first-page":"98","article-title":"A Taxonomy of AI techniques for security and privacy in cyber\u2013physical systems","volume":"3","author":"Bandi","year":"2024","journal-title":"J. Comput. Cogn. Eng."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Calabr\u00f2, A., Cambiaso, E., Cheminod, M., Bertolotti, I.C., Durante, L., Forestiero, A., Lombardi, F., Manco, G., Marchetti, E., and Orlando, A. (2024). A Methodological Approach to Securing Cyber-Physical Systems for Critical Infrastructures. Future Internet, 16.","DOI":"10.3390\/fi16110418"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"7936","DOI":"10.1109\/TCYB.2024.3411868","article-title":"Cascading Failure in Cyber-Physical Systems: A Review on Failure Modeling and Vulnerability Analysis","volume":"54","author":"He","year":"2024","journal-title":"IEEE Trans. Cybern."},{"key":"ref_9","first-page":"266","article-title":"Cascade failure modeling and resilience analysis of mine cyber physical systems under deliberate attacks","volume":"5","author":"Wang","year":"2024","journal-title":"J. Saf. Sci. Resil."},{"key":"ref_10","unstructured":"Secretary of the Air Force (2019). Air Force Policy Directive 10-24 Mission Assurance, Department of the Air Force."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Ahmad, M.A., Baryannis, G., and Hill, R. (2024). Defining Complex Adaptive Systems: An Algorithmic Approach. Systems, 12.","DOI":"10.3390\/systems12020045"},{"key":"ref_12","unstructured":"Zimmerman, B., Lindberg, C., and Plsek, P. (1998). A Complexity Science Primer: What Is Complexity Science and Why Should I Learn About It, VHA Inc.. Adapted From: Edgeware: Lessons From Complexity Science for Health Care Leaders."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Goldman, H., McQuaid, R., and Picciotto, J. (2011, January 15\u201317). Cyber resilience for mission assurance. Proceedings of the 2011 IEEE International Conference on Technologies for Homeland Security (HST), Waltham, MA, USA.","DOI":"10.1109\/THS.2011.6107877"},{"key":"ref_14","first-page":"18","article-title":"Mission Assurance in Joint All-Domain Command and Control","volume":"35","year":"2021","journal-title":"Air Space Power J."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Pereira, C., Marto, A., Ribeiro, R., Gon\u00e7alves, A., Rodrigues, N., Rabad\u00e3o, C., Costa, R.L.d.C., and Santos, L. (2025). Security and Privacy in Physical\u2013Digital Environments: Trends and Opportunities. Future Internet, 17.","DOI":"10.3390\/fi17020083"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"82482","DOI":"10.1109\/ACCESS.2024.3404264","article-title":"Automated knowledge-based cybersecurity risk assessment of cyber-physical systems","volume":"12","author":"Phillips","year":"2024","journal-title":"IEEE Access"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"102248","DOI":"10.1016\/j.cose.2021.102248","article-title":"Cyber security in the age of COVID-19: A timeline and analysis of cyber-crime and cyber-attacks during the pandemic","volume":"105","author":"Lallie","year":"2021","journal-title":"Comput. Secur."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"S47","DOI":"10.1080\/14616696.2020.1804973","article-title":"Cybercrime and shifts in opportunities during COVID-19: A preliminary analysis in the UK","volume":"23","author":"Moneva","year":"2021","journal-title":"Eur. Soc."},{"key":"ref_19","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_20","doi-asserted-by":"crossref","first-page":"124","DOI":"10.1016\/j.jik.2021.01.002","article-title":"Factors influencing blockchain adoption in supply chain management practices: A study based on the oil industry","volume":"6","author":"Aslam","year":"2021","journal-title":"J. Innov. Knowl."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"102549","DOI":"10.1016\/j.ipm.2021.102549","article-title":"Quantum-inspired blockchain-based cybersecurity: Securing smart edge utilities in IoT-based smart cities","volume":"58","author":"Mehmood","year":"2021","journal-title":"Inf. Process. Manag."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1007\/s10586-020-03200-4","article-title":"Blockchain technology in supply chain management: An empirical study of the factors affecting user adoption\/acceptance","volume":"24","author":"Alazab","year":"2021","journal-title":"Clust. Comput."},{"key":"ref_23","first-page":"100190","article-title":"A blockchain-based architecture for secure and trustworthy operations in the industrial Internet of Things","volume":"21","author":"Latif","year":"2021","journal-title":"J. Ind. Inf. Integr."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1949","DOI":"10.1109\/JBHI.2021.3075995","article-title":"An efficient ciphertext-policy weighted attribute-based encryption for the internet of health things","volume":"26","author":"Li","year":"2021","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s40820-021-00621-7","article-title":"Fully fabric-based triboelectric nanogenerators as self-powered human\u2013machine interactive keyboards","volume":"13","author":"Yi","year":"2021","journal-title":"Nano-Micro Lett."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"860","DOI":"10.1109\/TII.2020.2974520","article-title":"Deep learning-based DDoS-attack detection for cyber\u2013physical system over 5G network","volume":"17","author":"Hussain","year":"2020","journal-title":"IEEE Trans. Ind. Inform."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"453","DOI":"10.1016\/j.future.2021.01.022","article-title":"DIDDOS: An approach for detection and identification of Distributed Denial of Service (DDoS) cyberattacks using Gated Recurrent Units (GRU)","volume":"118","author":"Khaliq","year":"2021","journal-title":"Future Gener. Comput. Syst."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1803","DOI":"10.1109\/TNSM.2020.3014929","article-title":"Multi-stage optimized machine learning framework for network intrusion detection","volume":"18","author":"Injadat","year":"2020","journal-title":"IEEE Trans. Netw. Serv. Manag."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s40537-020-00390-x","article-title":"Resampling imbalanced data for network intrusion detection datasets","volume":"8","author":"Bagui","year":"2021","journal-title":"J. Big Data"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"106904","DOI":"10.1016\/j.epsr.2020.106904","article-title":"Ensemble machine learning models for the detection of energy theft","volume":"192","author":"Gunturi","year":"2021","journal-title":"Electr. Power Syst. Res."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Hemalatha, J., Roseline, S.A., Geetha, S., Kadry, S., and Dama\u0161evi\u010dius, R. (2021). An efficient densenet-based deep learning model for malware detection. Entropy, 23.","DOI":"10.3390\/e23030344"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1155\/2021\/6634811","article-title":"Explainable artificial intelligence (XAI) to enhance trust management in intrusion detection systems using decision tree model","volume":"2021","author":"Mahbooba","year":"2021","journal-title":"Complexity"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"102994","DOI":"10.1016\/j.scs.2021.102994","article-title":"A new distributed architecture for evaluating AI-based security systems at the edge: Network TON IoT datasets","volume":"72","author":"Moustafa","year":"2021","journal-title":"Sustain. Cities Soc."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"3179","DOI":"10.1007\/s13042-020-01241-0","article-title":"Ensemble machine learning approach for classification of IoT devices in smart home","volume":"12","author":"Gupta","year":"2021","journal-title":"Int. J. Mach. Learn. Cybern."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"29775","DOI":"10.1109\/ACCESS.2021.3058403","article-title":"Cyber-physical energy systems security: Threat modeling, risk assessment, resources, metrics, and case studies","volume":"9","author":"Zografopoulos","year":"2021","journal-title":"IEEE Access"},{"key":"ref_36","first-page":"82","article-title":"Cyber security awareness, knowledge and behavior: A comparative study","volume":"62","author":"Zwilling","year":"2022","journal-title":"J. Comput. Inf. Syst."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1016\/j.jmsy.2020.04.012","article-title":"Digital twin-based designing of the configuration, motion, control, and optimization model of a flow-type smart manufacturing system","volume":"58","author":"Liu","year":"2021","journal-title":"J. Manuf. Syst."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1124","DOI":"10.1080\/17517575.2018.1470259","article-title":"Contextual self-organizing of manufacturing process for mass individualization: A cyber-physical-social system approach","volume":"14","author":"Leng","year":"2020","journal-title":"Enterp. Inf. Syst."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"94","DOI":"10.1016\/j.jmsy.2020.04.013","article-title":"Digital twin-based smart assembly process design and application framework for complex products and its case study","volume":"58","author":"Yi","year":"2021","journal-title":"J. Manuf. Syst."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"36","DOI":"10.1016\/j.jmsy.2020.05.012","article-title":"How to model and implement connections between physical and virtual models for digital twin application","volume":"58","author":"Jiang","year":"2021","journal-title":"J. Manuf. Syst."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"102075","DOI":"10.1016\/j.rcim.2020.102075","article-title":"The connotation of digital twin, and the construction and application method of shop-floor digital twin","volume":"68","author":"Zhuang","year":"2021","journal-title":"Robot. Comput. Integr. Manuf."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1016\/j.jrurstud.2021.05.003","article-title":"Digital transformation of agriculture and rural areas: A socio-cyber-physical system framework to support responsibilisation","volume":"85","author":"Rijswijk","year":"2021","journal-title":"J. Rural Stud."},{"key":"ref_43","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":"Mamta","year":"2021","journal-title":"IEEE\/CAA J. Autom. Sin."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"11717","DOI":"10.1109\/JIOT.2021.3058946","article-title":"Fortified-chain: A blockchain-based framework for security and privacy-assured internet of medical things with effective access control","volume":"8","author":"Egala","year":"2021","journal-title":"IEEE Internet Things J."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"15694","DOI":"10.1109\/JIOT.2020.3047662","article-title":"A lightweight and robust secure key establishment protocol for internet of medical things in COVID-19 patients care","volume":"8","author":"Masud","year":"2020","journal-title":"IEEE Internet Things J."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"107284","DOI":"10.1016\/j.ress.2020.107284","article-title":"Fault diagnosis based on extremely randomized trees in wireless sensor networks","volume":"205","author":"Saeed","year":"2021","journal-title":"Reliab. Eng. Syst. Saf."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"1331","DOI":"10.1109\/TII.2020.2981549","article-title":"Distributed resilient control for energy storage systems in cyber\u2013physical microgrids","volume":"17","author":"Deng","year":"2020","journal-title":"IEEE Trans. Ind. Inform."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"1134","DOI":"10.1109\/TCYB.2019.2962601","article-title":"A secure adaptive control for cooperative driving of autonomous connected vehicles in the presence of heterogeneous communication delays and cyberattacks","volume":"51","author":"Petrillo","year":"2020","journal-title":"IEEE Trans. Cybern."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"5615","DOI":"10.1109\/TII.2020.3023430","article-title":"DeepFed: Federated deep learning for intrusion detection in industrial cyber\u2013physical systems","volume":"17","author":"Li","year":"2020","journal-title":"IEEE Trans. Ind. Inform."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"1496","DOI":"10.1109\/TII.2020.2994747","article-title":"Trustworthiness in industrial IoT systems based on artificial intelligence","volume":"17","author":"Lv","year":"2020","journal-title":"IEEE Trans. Ind. Inform."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"5790","DOI":"10.1109\/TII.2020.3047675","article-title":"Siamese neural network based few-shot learning for anomaly detection in industrial cyber-physical systems","volume":"17","author":"Zhou","year":"2020","journal-title":"IEEE Trans. Ind. Inform."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"2665","DOI":"10.1109\/TCSI.2021.3071341","article-title":"Finite-time event-triggered control for semi-Markovian switching cyber-physical systems with FDI attacks and applications","volume":"68","author":"Qi","year":"2021","journal-title":"IEEE Trans. Circuits Syst. I Regul. Pap."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"102","DOI":"10.1016\/j.spc.2020.07.018","article-title":"Expected impact of industry 4.0 technologies on sustainable development: A study in the context of Brazil\u2019s plastic industry","volume":"25","author":"Nara","year":"2021","journal-title":"Sustain. Prod. Consum."},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Bonilla, S.H., Silva, H.R., Terra da Silva, M., Franco Gon\u00e7alves, R., and Sacomano, J.B. (2018). Industry 4.0 and sustainability implications: A scenario-based analysis of the impacts and challenges. Sustainability, 10.","DOI":"10.3390\/su10103740"},{"key":"ref_55","first-page":"255","article-title":"How does Industry 4.0 contribute to operations management?","volume":"35","author":"Fettermann","year":"2018","journal-title":"J. Ind. Prod. Eng."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"372","DOI":"10.1016\/j.psep.2018.05.017","article-title":"Making the links among environmental protection, process safety, and industry 4.0","volume":"117","author":"Junior","year":"2018","journal-title":"Process. Saf. Environ. Prot."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1016\/j.procir.2014.06.036","article-title":"Predictive analytics model for power consumption in manufacturing","volume":"15","author":"Shin","year":"2014","journal-title":"Procedia CIRP"},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"644","DOI":"10.1016\/j.procir.2017.11.124","article-title":"Environmental sustainability of cyber physical production systems","volume":"69","author":"Thiede","year":"2018","journal-title":"Procedia CIRP"},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"125391","DOI":"10.1016\/j.jclepro.2020.125391","article-title":"A blockchain- and IoT-based smart product-service system for the sustainability of prefabricated housing construction","volume":"286","author":"Li","year":"2021","journal-title":"J. Clean. Prod."},{"key":"ref_60","first-page":"10","article-title":"Answering the Cybersecurity Issues: Confidentiality, Integrity, and Availability","volume":"15","author":"Edwards","year":"2020","journal-title":"J. Strateg. Innov. Sustain."},{"key":"ref_61","first-page":"1","article-title":"Using the CIA and AAA models to explain cybersecurity activities","volume":"6","author":"Nweke","year":"2017","journal-title":"PM World J."},{"key":"ref_62","unstructured":"Roelofs, R. (2019). Measuring Generalization and Overfitting in Machine Learning, University of California."},{"key":"ref_63","unstructured":"Mersinas, K., Sobb, T., Sample, C., Bakdash, J.Z., and Ormrod, D. (November, January 31). Training Data and Rationality. Proceedings of the ECIAIR 2019 European Conference on the Impact of Artificial Intelligence and Robotics, Oxford, UK."},{"key":"ref_64","doi-asserted-by":"crossref","unstructured":"Huang, C., Marshall, J., Wang, D., and Dong, M. (2016, January 23\u201327). Towards reliable social sensing in cyber-physical-social systems. Proceedings of the 2016 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), Chicago, IL, USA.","DOI":"10.1109\/IPDPSW.2016.132"},{"key":"ref_65","unstructured":"Mirza, I.B. (2024). Intersecting Sensor and Social Media Information Spaces for Comprehensive Situation Awareness. [Ph.D. Thesis, School of Science, Computing And Engineering Technologies, Swinburne University of Technology]."},{"key":"ref_66","doi-asserted-by":"crossref","unstructured":"Mirza, I.B., Georgakopoulos, D., and Yavari, A. (2023). Cyber-physical-social awareness platform for comprehensive situation awareness. Sensors, 23.","DOI":"10.3390\/s23020822"},{"key":"ref_67","doi-asserted-by":"crossref","unstructured":"Revathi, S., Raja, J., Mohanraj, M., Malathi, K., Mallala, B., and Vidhya, R. (2024, January 18\u201320). Challenges in Cyber Physical Social Systems and Internet of Things. Proceedings of the 2024 5th International Conference on Smart Electronics and Communication (ICOSEC), Trichy, India.","DOI":"10.1109\/ICOSEC61587.2024.10722103"},{"key":"ref_68","doi-asserted-by":"crossref","unstructured":"Gruber, T. (2009). What is an Ontology?. Encyclopedia of Database Systems, Springer.","DOI":"10.1007\/978-0-387-39940-9_1318"},{"key":"ref_69","unstructured":"Neuhaus, F. (2018). What is an Ontology?. arXiv."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1016\/j.diin.2006.06.008","article-title":"A cyber forensics ontology: Creating a new approach to studying cyber forensics","volume":"3","author":"Brinson","year":"2006","journal-title":"Digit. Investig."},{"key":"ref_71","first-page":"64","article-title":"Towards a Cyber Ontology for Insider Threats in the Financial Sector","volume":"6","author":"Kul","year":"2015","journal-title":"J. Wirel. Mob. Netw. Ubiquitous Comput. Dependable Appl."},{"key":"ref_72","unstructured":"Obrst, L., Chase, P., and Markeloff, R. (2012, January 24\u201325). Developing an Ontology of the Cyber Security Domain. Proceedings of the STIDS, Fairfax, VA, USA."},{"key":"ref_73","first-page":"26","article-title":"Towards a Human Factors Ontology for Cyber Security","volume":"2015","author":"Oltramari","year":"2015","journal-title":"Stids"},{"key":"ref_74","unstructured":"Syed, Z., Padia, A., Finin, T., Mathews, L., and Joshi, A. (2016, January 12\u201313). UCO: A unified cybersecurity ontology. Proceedings of the Workshops at the Thirtieth AAAI Conference on Artificial Intelligence, Phoenix, AZ, USA."},{"key":"ref_75","doi-asserted-by":"crossref","unstructured":"Varvarigou, D., Espes, D., and Bersano, G. (2023). Ontology-Based Solution for Handling Safety and Cybersecurity Interdependency in Safety-Critical Systems. Latest Advances and New Visions of Ontology in Information Science, IntechOpen. Book Section 3.","DOI":"10.5772\/intechopen.110333"},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"109685","DOI":"10.1016\/j.ecolmodel.2021.109685","article-title":"Challenges, tasks, and opportunities in modeling agent-based complex systems","volume":"457","author":"An","year":"2021","journal-title":"Ecol. Model."},{"key":"ref_77","doi-asserted-by":"crossref","unstructured":"Bemthuis, R., Mes, M., Iacob, M.E., and Havinga, P. (2020, January 14\u201318). Using agent-based simulation for emergent behavior detection in cyber-physical systems. Proceedings of the 2020 Winter Simulation Conference (WSC), Orlando, FL, USA.","DOI":"10.1109\/WSC48552.2020.9383956"},{"key":"ref_78","unstructured":"Kotenko, I., Konovalov, A., and Shorov, A. (June, January 29). Agent-based modeling and simulation of botnets and botnet defense. Proceedings of the Conference on Cyber Conflict, Tallinn, Estonia."},{"key":"ref_79","unstructured":"Kotenko, I., and Mankov, E. (2003, January 14). Agent-Based Modeling and Simulation of Computer Network Attacks. Proceedings of the Fourth International Workshop on Agent-Based Simulation, Melbourne, Australia."},{"key":"ref_80","doi-asserted-by":"crossref","unstructured":"Novak, P., Kadera, P., and Wimmer, M. (2017, January 21\u201323). Agent-based modeling and simulation of hybrid cyber-physical systems. Proceedings of the 2017 3rd IEEE International Conference on Cybernetics (CYBCONF), Exeter, UK.","DOI":"10.1109\/CYBConf.2017.7985755"},{"key":"ref_81","unstructured":"Rafferty, L. (2022). Agent-Based Modeling Framework for Adaptive Cyber Defence of the Internet of Things. [Ph.D. Thesis, University of Ontario Institute of Technology (Ontario Tech University)]."},{"key":"ref_82","unstructured":"Mata, O., Ponce, P., McDaniel, T., M\u00e9ndez, J.I., Peffer, T., and Molina, A. (September, January 30). Smart city concept based on cyber-physical social systems with hierarchical ethical agents approach. Proceedings of the International Conference On Human-Computer Interaction, Bari, Italy."},{"key":"ref_83","doi-asserted-by":"crossref","unstructured":"\u00d6ren, T. (2022). Security of Cyber-Physical-Social Systems: Impact of Simulation-Based Systems Engineering, Artificial Intelligence, Human Involvement, and Ethics. Advances in Computing, Informatics, Networking and Cybersecurity: A Book Honoring Professor Mohammad S. Obaidat\u2019s Significant Scientific Contributions, Springer.","DOI":"10.1007\/978-3-030-87049-2_26"},{"key":"ref_84","doi-asserted-by":"crossref","unstructured":"Farid, K., and Sakr, N. (2021, January 16\u201318). Few-Shot System Identification for Reinforcement Learning. Proceedings of the 2021 6th Asia-Pacific Conference on Intelligent Robot Systems (ACIRS), Tokyo, Japan.","DOI":"10.1109\/ACIRS52449.2021.9519314"},{"key":"ref_85","unstructured":"Luo, B., Zhang, Y., Dubey, A., and Mukhopadhyay, A. (2024). Act as you learn: Adaptive decision-making in non-stationary markov decision processes. arXiv."},{"key":"ref_86","unstructured":"Sinha, S., Vaidya, U., and Yeung, E. (2021). On few shot learning of dynamical systems: A Koopman operator theoretic approach. arXiv."},{"key":"ref_87","doi-asserted-by":"crossref","first-page":"486","DOI":"10.1109\/TBDATA.2024.3350542","article-title":"Few-shot learning with multi-granularity knowledge fusion and decision-making","volume":"10","author":"Su","year":"2024","journal-title":"IEEE Trans. Big Data"},{"key":"ref_88","doi-asserted-by":"crossref","unstructured":"Zaman, M., Eini, R., Zohrabi, N., and Abdelwahed, S. (2022, January 26\u201329). A Decision Support System for Cyber Physical Systems under Disruptive Events: Smart Building Application. Proceedings of the 2022 IEEE International Smart Cities Conference (ISC2), Pafos, Cyprus.","DOI":"10.1109\/ISC255366.2022.9922493"},{"key":"ref_89","doi-asserted-by":"crossref","first-page":"106572","DOI":"10.1016\/j.chb.2020.106572","article-title":"The importance of the assurance that \u201chumans are still in the decision loop\u201d for public trust in artificial intelligence: Evidence from an online experiment","volume":"114","author":"Aoki","year":"2021","journal-title":"Comput. Hum. Behav."},{"key":"ref_90","doi-asserted-by":"crossref","unstructured":"Kathiresan, G. (2025). Human-in-the-Loop Testing for LLM-Integrated Software: A Quality Engineering Framework for Trust and Safety. Authorea Prepr.","DOI":"10.36227\/techrxiv.174702077.78864934\/v1"},{"key":"ref_91","first-page":"473","article-title":"D-bias: A causality-based human-in-the-loop system for tackling algorithmic bias","volume":"29","author":"Ghai","year":"2022","journal-title":"IEEE Trans. Vis. Comput. Graph."},{"key":"ref_92","doi-asserted-by":"crossref","first-page":"820","DOI":"10.1109\/TSE.1987.233493","article-title":"Theory of modules","volume":"SE-13","author":"Gannon","year":"1987","journal-title":"IEEE Trans. Softw. Eng."},{"key":"ref_93","doi-asserted-by":"crossref","unstructured":"Field, A. (2023). Risk Management and ISO 31000: A Pocket Guide, IT Governance Publishing.","DOI":"10.2307\/jj.1094269"},{"key":"ref_94","doi-asserted-by":"crossref","first-page":"881","DOI":"10.1111\/j.1539-6924.2010.01442.x","article-title":"ISO 31000: 2009\u2014setting a new standard for risk management","volume":"30","author":"Purdy","year":"2010","journal-title":"Risk Anal. Int. J."},{"key":"ref_95","doi-asserted-by":"crossref","first-page":"208","DOI":"10.1016\/j.ress.2014.10.006","article-title":"Development of a cyber security risk model using Bayesian networks","volume":"134","author":"Shin","year":"2015","journal-title":"Reliab. Eng. Syst. Saf."},{"key":"ref_96","doi-asserted-by":"crossref","first-page":"323","DOI":"10.1016\/j.cose.2017.09.011","article-title":"Improving risk assessment model of cyber security using fuzzy logic inference system","volume":"74","author":"Alali","year":"2018","journal-title":"Comput. Secur."},{"key":"ref_97","unstructured":"McQueen, M.A., Boyer, W.F., Flynn, M.A., and Beitel, G.A. Time-to-compromise model for cyber risk reduction estimation. Proceedings of the Quality of Protection: Security Measurements and Metrics."},{"key":"ref_98","doi-asserted-by":"crossref","unstructured":"Palko, D., Babenko, T., Bigdan, A., Kiktev, N., Hutsol, T., Kubo\u0144, M., Hnatiienko, H., Tabor, S., Gorbovy, O., and Borusiewicz, A. (2023). Cyber security risk modeling in distributed information systems. Appl. Sci., 13.","DOI":"10.3390\/app13042393"},{"key":"ref_99","doi-asserted-by":"crossref","first-page":"997","DOI":"10.1007\/s10796-017-9808-5","article-title":"Cyber risk assessment and mitigation (CRAM) framework using logit and probit models for cyber insurance","volume":"21","author":"Mukhopadhyay","year":"2019","journal-title":"Inf. Syst. Front."},{"key":"ref_100","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1007\/s13437-019-00162-2","article-title":"MaCRA: A model-based framework for maritime cyber-risk assessment","volume":"18","author":"Tam","year":"2019","journal-title":"WMU J. Marit. Aff."},{"key":"ref_101","doi-asserted-by":"crossref","first-page":"101600","DOI":"10.1016\/j.cose.2019.101600","article-title":"Cyber risk assessment in cloud provider environments: Current models and future needs","volume":"87","author":"Akinrolabu","year":"2019","journal-title":"Comput. Secur."},{"key":"ref_102","doi-asserted-by":"crossref","unstructured":"Avc\u0131, \u0130., and Koca, M. (2024). Intelligent Transportation System Technologies, Challenges and Security. Appl. Sci., 14.","DOI":"10.3390\/app14114646"},{"key":"ref_103","doi-asserted-by":"crossref","unstructured":"Lee, K., Hong, D., Kim, J., Cha, D., Choi, H., Moon, J., and Moon, C. (2023). Road-network-based event information system in a cooperative ITS Environment. Electronics, 12.","DOI":"10.3390\/electronics12112448"},{"key":"ref_104","doi-asserted-by":"crossref","unstructured":"Levina, A.I., Dubgorn, A.S., and Iliashenko, O.Y. (2017, January 17\u201319). Internet of things within the service architecture of intelligent transport systems. Proceedings of the 2017 European Conference on Electrical Engineering and Computer Science (EECS), Bern, Switzerland.","DOI":"10.1109\/EECS.2017.72"}],"container-title":["Future Internet"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1999-5903\/17\/7\/282\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T17:58:41Z","timestamp":1760032721000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1999-5903\/17\/7\/282"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6,25]]},"references-count":104,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2025,7]]}},"alternative-id":["fi17070282"],"URL":"https:\/\/doi.org\/10.3390\/fi17070282","relation":{},"ISSN":["1999-5903"],"issn-type":[{"value":"1999-5903","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,6,25]]}}}