{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,27]],"date-time":"2026-05-27T18:29:33Z","timestamp":1779906573784,"version":"3.53.1"},"reference-count":81,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2024,4,30]],"date-time":"2024-04-30T00:00:00Z","timestamp":1714435200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>Cyber competitions are usually team activities, where team performance not only depends on the members\u2019 abilities but also on team collaboration. This seems intuitive, especially given that team formation is a well-studied discipline in competitive sports and project management, but unfortunately, team performance and team formation strategies are rarely studied in the context of cybersecurity and cyber competitions. Since cyber competitions are becoming more prevalent and organized, this gap becomes an opportunity to formalize the study of team performance in the context of cyber competitions. This work follows a cross-validating two-approach methodology. The first is the computational modeling of cyber competitions using Agent-Based Modeling. Team members are modeled, in NetLogo, as collaborating agents competing over a network in a red team\/blue team match. Members\u2019 abilities, team interaction and network properties are parametrized (inputs), and the match score is reported as output. The second approach is grounded in the literature of team performance (not in the context of cyber competitions), where a theoretical framework is built in accordance with the literature. The results of the first approach are used to build a causal inference model using Structural Equation Modeling. Upon comparing the causal inference model to the theoretical model, they showed high resemblance, and this cross-validated both approaches. Two main findings are deduced: first, the body of literature studying teams remains valid and applicable in the context of cyber competitions. Second, coaches and researchers can test new team strategies computationally and achieve precise performance predictions. The targeted gap used methodology and findings which are novel to the study of cyber competitions.<\/jats:p>","DOI":"10.3390\/e26050384","type":"journal-article","created":{"date-parts":[[2024,4,30]],"date-time":"2024-04-30T09:50:07Z","timestamp":1714470607000},"page":"384","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["CCTFv2: Modeling Cyber Competitions"],"prefix":"10.3390","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3270-7225","authenticated-orcid":false,"given":"Basheer","family":"Qolomany","sequence":"first","affiliation":[{"name":"Cyber Systems Department, University of Nebraska at Kearney, Kearney, NE 68849, USA"},{"name":"School of Information Technology, University of Cincinnati, Cincinnati, OH 45221, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tristan J.","family":"Calay","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Information Systems, Saginaw Valley State University, University Center, MI 48710, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7616-9182","authenticated-orcid":false,"given":"Liaquat","family":"Hossain","sequence":"additional","affiliation":[{"name":"School of Computing, Montclair State University, Montclair, NJ 07043, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2783-297X","authenticated-orcid":false,"given":"Aos","family":"Mulahuwaish","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Information Systems, Saginaw Valley State University, University Center, MI 48710, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3482-9154","authenticated-orcid":false,"given":"Jacques","family":"Bou Abdo","sequence":"additional","affiliation":[{"name":"School of Information Technology, University of Cincinnati, Cincinnati, OH 45221, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,4,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"10832","DOI":"10.1038\/s41598-019-47210-8","article-title":"Structural entropy: Monitoring correlation-based networks over time with application to financial markets","volume":"9","author":"Almog","year":"2019","journal-title":"Sci. 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