LDA 토픽 모델링을 활용안 정보보안 분야 동향 분석
Analysis of trends in information security using LDA topic modeling
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참고문헌
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초록
컴퓨터 관련 기술이 급변하는 환경에서 사이버 위협들은 새로운 기술과 함께 고도화되고 다양화되어 지속해서 등장하고 있다. 이에 본 연구에서는 보안 관련 뉴스 기사를 수집해서 LDA 토픽모델링을 진행해 동향을 살펴보고자 한다. 이를 위해 2020년 1월부터 2023년 8월까지의 뉴스 기사를 수집하였으며 LDA 분석을 통해 주요 토픽을 도출하였다. 이후 토픽별 흐름을 파악하고 주요기점에 대해 분석하였다. 분석 결과를 통해 2021년의 랜섬웨어 공격과 2023년의 가상자산거래소해킹이 최근 보안 분야에서 큰 이슈인 것을 파악할 수 있다. 이를 통해 보안 이슈에 대한 동향을확인하고, 앞으로 어떤 연구에 집중해야 하는지 확인해 볼 수 있다. 또한 최신 위협을 인지하고, 적절한 대응 전략을 지원할 수 있으며 효과적인 보안 대책의 개발에 기여할 것으로 기대된다.
Abstract
In an environment where computer-related technologies are rapidly changing, cyber threats continue to emerge as they are advanced and diversified along with new technologies. Therefore, in this study, we would like to collect security-related news articles, conduct LDA topic modeling, and examine trends. To that end, news articles from January 2020 to August 2023 were collected and major topics were derived through LDA analysis. After that, the flow by topic was grasped and the main origin was analyzed. The analysis results show that ransomware attacks in 2021 and hacking of virtual asset exchanges in 2023 are major issues in the recent security sector. This allows you to check trends in security issues and see what research should be focused on in the future. It is also expected to be able to recognize the latest threats and support appropriate response strategies, contributing to the development of effective security measures.
참고문헌 (18)
- Cho Sung Phil, "The Study on Threats of Information Security and Their Solutions in the Fourth Industrial Revolution", Korean Security Journal, (51), pp.9~36 (2017)[DOI]
- CK academy, "Analysis of Global Research Trend on Information Security", Journal of the Korea Institute of Information and Communication Engineering, 19(5), pp.1110~1116 (2015)[DOI]
- Seung-Tae Yoo, "Analysis of Domestic Industrial Security Trends using LDA Topic Modeling", Korean Journal of Industrial Security, 10(2), pp.79~103 (2020)[DOI]
- Kyoungsik Na, "Trends of South Korea’s Informatization and Libraries’ Role Based on Newspaper Big Data", The Journal of the Korea Contents Association, 18(9), pp.14~33 (2018)[DOI]
- Daemin Park, "Automated Time Series Content Analysis with News Big Data Analytics : Analyzing Sources and Quotes in One Million News Articles for 26 Years", Korean Journal of Journalism & Communication Studies, 60(5), pp.353~407 (2016)[DOI]
- Keon Chul Park, "A Study on the Research Trends for Smart City using Topic Modeling", Journal of Internet Computing and Services, 20(3), pp.119~128 (2019)[DOI]
- Sung-Chan Jun, "Technology Development Strategy of Piggyback Transportation System Using Topic Modeling Based on LDA Algorithm", Journal of The Korea Society of Computer and Information, 25(12), pp.261~270 (2020)[DOI]
- David M. Blei, "Latent dirichlet allocation", Journal of Machine Learning Research, 3, pp.993~1022 (2003)[DOI]
- Lei Fang, "Congestion measurement in nonparametric analysis under the weakly disposable technology", European Journal of Operational Research, 245, pp.203~208 (2015)[DOI]
- Gapcheol Kim, "Research Trends of Regional Geography Education Using Topic Modeling", Social Studies Education, 58(4), pp.49~67 (2019)[DOI]
- David Newman, "Automatic Evaluation of Topic Coherence", Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics, pp.100~108 (2010)
- Hyo-Jun Yun, "Introduction of topic modeling for extracting potential information from unstructured text data: Issue analysis on news article of dementia-related physical activity", 30(3), pp.501~512 (2019)[DOI]
- Yoonhwan Oh, "Analysis of global trends on smart manufacturing technology using topic modeling", Journal of Korea Society of Industrial Information Systems, 27(4), pp.65~79 (2022)[DOI]
- Sievert, Carson, "LDAvis : A method for visualizing and interpreting topics", Proceedings of the Workshop on Interactive Language Learning, Visualization, and Interfaces, pp.63~70 (2014)
- KIM KEE OK, "Analysis of Research Trends in Consumer Science through Text Mining", Journal of Consumer Studies, 35(5), pp.19~47 (2020)[DOI]
- PARK JUNHYEONG, "Comparison of Topic Modeling Methods for Analyzing Research Trends of Archives Management in Korea : focused on LDA and HDP", Journal of Korean Library and Information Science Society, 48(4), pp.235~258 (2017)[DOI]
- Cyber Threat Trend Report for the Second Half of 2023, "Korea Internet & Security Agency", Korea Internet & Security Agency, Ministry of Science and ICT, 19~28 (2021)