Assessing the Role of User Computer Self-Efficacy, Cybersecurity Countermeasures Awareness, and Cybersecurity Skills toward Computer Misuse Intention at Government Agencies

摘要

Cybersecurity threats and vulnerabilities are causing substantial financial losses for governments and organizations all over the world. Cybersecurity criminals are stealing more than one billion dollars from banks every year by exploiting vulnerabilities caused by bank usersu27 computer misuse. Cybersecurity breaches are threatening the common welfare of citizens since more and more terrorists are using cyberterrorism to target critical infrastructures (e.g., transportation, telecommunications, power, nuclear plants, water supply, banking) to coerce the targeted government and its people to accomplish their political objectives. Cyberwar is another major concern that nations around the world are struggling to get ready to fight. It has been found that intentional and unintentional usersu27 misuse of information systems (IS) resources represents about 50% to 75% of cybersecurity threats and vulnerabilities to organizations. Computer Crime and Security Survey revealed that nearly 60% of security breaches occurred from inside the organization by users.Computer users are one of the weakest links in the information systems security chain, because users seem to have very limited or no knowledge of user computer self-efficacy (CSE), cybersecurity countermeasures awareness (CCA), and cybersecurity skills (CS). Usersu27 CSE, CCA, and CS play an important role in usersu27 computer misuse intention (CMI). CMI can be categorized as unauthorized access, use, disruption, modification, disclosure, inspection, recording, or destruction of information system data. This dissertation used a survey to empirically assess usersu27 CSE, CCA, CS, and computer misuse intention (CMI) at government agencies. This study used Partial Least Square (PLS) technique to measure the fit of a theoretical model that includes seven independent latent variables (CSE, UAS-P, UAS-T, UAC-M, CCS, CIS, u26 CAS) and their influences on the dependent variable CMI. Also, PLS was used to examine if the six control variables (age, gender, job function, education level, length of working in the organization, u26 military status such as veteran) had any significant impact on CMI.This study included data collected from 185 employees of a local and state transportation agency from a large metropolitan in the northeastern United States. Participants received an email invitation to take the Web-based survey. PLS was used to test the four research hypotheses. The results of the PLS model showed that UAC-M and CIS were significant contributors (p