{"title":"A Comprehensive Bibliometric Analysis of Insider Threat Scholarship","authors":"Luke J. Osterritter;Kathleen M. Carley","doi":"10.1109/TCSS.2026.3705576","DOIUrl":null,"url":null,"abstract":"The study of insider threat and insider risk, that of the risk trusted individuals may misuse authorized access to harm their organizations, is a relatively nascent academic field. It is a multidisciplinary problem; one of computer science, information science, and cybersecurity, as well as business, management, organizational theory, psychology, sociology, human behavior, and beyond. Existing reviews have addressed narrow subdomains, such as detection methods, taxonomies, or behavioral modeling, leaving the broader structure of the field, namely its key contributors, institutional networks, topical landscape, and interdisciplinary composition, largely unexamined. This study addresses that gap through a large-scale bibliometric analysis of insider threat and risk scholarship. We assemble a corpus of 3769 publications from 1977 to 2023, drawn from six citation databases and multiple grey literature sources, which we analyze using established bibliometric and network analytical techniques. Our findings reveal a field that has grown steadily since the early 2000s, bolstered by landmark policy events, institutional investments, and high-profile instances of insider threat. The co-authorship network identifies an “invisible college” of scholars, with a large contingent of researchers anchored by universities across nations and several U.S. national laboratories, federally funded research centers, and university-affiliated research centers. Critically, we find a pronounced imbalance in research focus where the vast majority of publications address technical solutions, while a notably smaller amount of work addresses behavioral, organizational, or hybrid approaches—despite broad consensus in the literature that effective insider threat mitigation requires both. Topic network analysis further reveals a well-defined core of research themes, alongside underexplored areas in organizational psychology, positive deterrence, and socio-technical integration. Publication venue analysis reveals a more balanced distribution between conferences and journals than is typical of computer science research, reflecting the field’s interdisciplinary nature. Based on these findings, we identify priority research directions and development of the field. This work provides the first comprehensive bibliometric characterization of insider threat and risk scholarship, offering the research community a foundational look at where the discipline stands and how it should move forward.","PeriodicalId":13044,"journal":{"name":"IEEE Transactions on Computational Social Systems","volume":"13 5","pages":"5564-5580"},"PeriodicalIF":4.6000,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Computational Social Systems","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/11599420/","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2026/7/8 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"COMPUTER SCIENCE, CYBERNETICS","Score":null,"Total":0}
引用次数: 0
Abstract
The study of insider threat and insider risk, that of the risk trusted individuals may misuse authorized access to harm their organizations, is a relatively nascent academic field. It is a multidisciplinary problem; one of computer science, information science, and cybersecurity, as well as business, management, organizational theory, psychology, sociology, human behavior, and beyond. Existing reviews have addressed narrow subdomains, such as detection methods, taxonomies, or behavioral modeling, leaving the broader structure of the field, namely its key contributors, institutional networks, topical landscape, and interdisciplinary composition, largely unexamined. This study addresses that gap through a large-scale bibliometric analysis of insider threat and risk scholarship. We assemble a corpus of 3769 publications from 1977 to 2023, drawn from six citation databases and multiple grey literature sources, which we analyze using established bibliometric and network analytical techniques. Our findings reveal a field that has grown steadily since the early 2000s, bolstered by landmark policy events, institutional investments, and high-profile instances of insider threat. The co-authorship network identifies an “invisible college” of scholars, with a large contingent of researchers anchored by universities across nations and several U.S. national laboratories, federally funded research centers, and university-affiliated research centers. Critically, we find a pronounced imbalance in research focus where the vast majority of publications address technical solutions, while a notably smaller amount of work addresses behavioral, organizational, or hybrid approaches—despite broad consensus in the literature that effective insider threat mitigation requires both. Topic network analysis further reveals a well-defined core of research themes, alongside underexplored areas in organizational psychology, positive deterrence, and socio-technical integration. Publication venue analysis reveals a more balanced distribution between conferences and journals than is typical of computer science research, reflecting the field’s interdisciplinary nature. Based on these findings, we identify priority research directions and development of the field. This work provides the first comprehensive bibliometric characterization of insider threat and risk scholarship, offering the research community a foundational look at where the discipline stands and how it should move forward.
期刊介绍:
IEEE Transactions on Computational Social Systems focuses on such topics as modeling, simulation, analysis and understanding of social systems from the quantitative and/or computational perspective. "Systems" include man-man, man-machine and machine-machine organizations and adversarial situations as well as social media structures and their dynamics. More specifically, the proposed transactions publishes articles on modeling the dynamics of social systems, methodologies for incorporating and representing socio-cultural and behavioral aspects in computational modeling, analysis of social system behavior and structure, and paradigms for social systems modeling and simulation. The journal also features articles on social network dynamics, social intelligence and cognition, social systems design and architectures, socio-cultural modeling and representation, and computational behavior modeling, and their applications.