Cyber Strategic Technology Key Topics and Trend Analysis

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Seung-Yeon Hwang , Jeong-Joon Kim


In response to evolving societal needs and advancements in science and technology, there is active engagement in research dedicated to forecasting and analyzing future technologies anticipated to arise across various scientific and technological domains. This paper utilizes the titles and summary information of about 4,200 papers published in journals in the field of information security to analyze key topics and trends in strategic technology in the field of cybersecurity among various fields of science and technology. In addition, Latent Dirichlet Allocation (LDA) is used to analyze key topics and keywords of cyber strategic technology, and Dynamic Topic Modeling (DTM) is used to analyze trends. By analyzing it on a yearly basis from 2010 to 2020, promising and unpromising fields could be identified. The results derived from the subject extraction engine developed in this study and the opinions of experts in each field are expected to achieve more reliable results, and the strategic technology of the future cyber strategy field is analyzed through cyber strategy technology prediction model research. Based on this accumulated strategic analysis information, it is expected that it will be able to predict new convergence strategies according to environmental changes and strengthen all of the world's cyber response capabilities and competitiveness.

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