{"title":"An Empirical Comparison of Malicious Insiders and Benign Insiders","authors":"Nan Liang, David P. Biros, Andy Luse","doi":"10.1080/08874417.2023.2251427","DOIUrl":null,"url":null,"abstract":"Malicious insiders continue to pose a significant threat to organizations. With their knowledge, privilege, and access to organizational resources, malicious insiders can attack the organization easier than outsiders, bypassing security measures. Current research about malicious insiders’ traits is often based on a limited number of cases and lacking empirical validation. With few exceptions, most research focuses on the effects of individual traits without investigation of their interactions. To identify the effects of these traits and their interactions, this study employs text mining to analyze 133 real-world malicious insider cases by comparing how the media portray malicious insiders to how the media portray benign insiders. This study sheds light on the predictive power of common traits of malicious insiders. Also, the interaction effects of some traits indicate that although they are not significant at the unary level, their co-occurrence differentiates malicious insiders with benign insiders as portrayed in the media.","PeriodicalId":54855,"journal":{"name":"Journal of Computer Information Systems","volume":"45 1","pages":"0"},"PeriodicalIF":2.5000,"publicationDate":"2023-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Computer Information Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/08874417.2023.2251427","RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
Malicious insiders continue to pose a significant threat to organizations. With their knowledge, privilege, and access to organizational resources, malicious insiders can attack the organization easier than outsiders, bypassing security measures. Current research about malicious insiders’ traits is often based on a limited number of cases and lacking empirical validation. With few exceptions, most research focuses on the effects of individual traits without investigation of their interactions. To identify the effects of these traits and their interactions, this study employs text mining to analyze 133 real-world malicious insider cases by comparing how the media portray malicious insiders to how the media portray benign insiders. This study sheds light on the predictive power of common traits of malicious insiders. Also, the interaction effects of some traits indicate that although they are not significant at the unary level, their co-occurrence differentiates malicious insiders with benign insiders as portrayed in the media.
期刊介绍:
The Journal of Computer Information Systems (JCIS) aims to publish manuscripts that explore information systems and technology research and thus develop computer information systems globally.
We encourage manuscripts that cover the following topic areas:
-Analytics, Business Intelligence, Decision Support Systems in Computer Information Systems
- Mobile Technology, Mobile Applications
- Human-Computer Interaction
- Information and/or Technology Management, Organizational Behavior & Culture
- Data Management, Data Mining, Database Design and Development
- E-Commerce Technology and Issues in computer information systems
- Computer systems enterprise architecture, enterprise resource planning
- Ethical and Legal Issues of IT
- Health Informatics
- Information Assurance and Security--Cyber Security, Cyber Forensics
- IT Project Management
- Knowledge Management in computer information systems
- Networks and/or Telecommunications
- Systems Analysis, Design, and/or Implementation
- Web Programming and Development
- Curriculum Issues, Instructional Issues, Capstone Courses, Specialized Curriculum Accreditation
- E-Learning Technologies, Analytics, Future