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논문KCI 등재

국방 지능형 사이버위협 대응시스템의 수용의도에 영향을 미치는 요인에 관한 연구: 인공지능 기술특성을 중심으로

A Study on the Fators Affecting the Intention to Accept Defense Intelligent Cyber Threat Response System: Focused on AI Technology Characteristics

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초록

Purpose: The purpose of this study is to examine the factors affecting the intention to accept Defense Intelligent Cyber Threat Response System based on AI Technology Characteristics from the user's point of view. Methods: The study conducted a survey of experienced people targeting defense cyber personnel performing national defense cyber operations, and valid 357 data were analyzed by SPSS (ver 22.0) and R (ver 4.1.0) program packages. Results: As a result of the empirical analysis, it was found that among the AI technological characteristics of the Defense Intelligent Cyber Threat Response System, speed, expertise, and reliability, in that order, had an impact on performance expectancy. In terms of effort expectancy, reliability, expertise, and accuracy were found to be the influencing factors. Additionally, social influence and performance expectancy were found to have a positive effect on the intention to adopt the Defense Intelligent Cyber Threat Response System. Conclusion: This study is significant in that it structurally analyzes the factors affecting system adoption in the defense environment from a user perspective, thereby laying the foundation for the practical utilization and dissemination of the technology. Beyond merely improving technological performance, it is expected to provide strategies for the effective adoption and utilization of the Defense Intelligent Cyber Threat Response System within actual defense organizations.

Abstract

Purpose: The purpose of this study is to examine the factors affecting the intention to accept Defense Intelligent Cyber Threat Response System based on AI Technology Characteristics from the user's point of view. Methods: The study conducted a survey of experienced people targeting defense cyber personnel performing national defense cyber operations, and valid 357 data were analyzed by SPSS (ver 22.0) and R (ver 4.1.0) program packages. Results: As a result of the empirical analysis, it was found that among the AI technological characteristics of the Defense Intelligent Cyber Threat Response System, speed, expertise, and reliability, in that order, had an impact on performance expectancy. In terms of effort expectancy, reliability, expertise, and accuracy were found to be the influencing factors. Additionally, social influence and performance expectancy were found to have a positive effect on the intention to adopt the Defense Intelligent Cyber Threat Response System. Conclusion: This study is significant in that it structurally analyzes the factors affecting system adoption in the defense environment from a user perspective, thereby laying the foundation for the practical utilization and dissemination of the technology. Beyond merely improving technological performance, it is expected to provide strategies for the effective adoption and utilization of the Defense Intelligent Cyber Threat Response System within actual defense organizations.

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