AN ANALYSIS OF PHISHING CASES USING TEXT MINING
- Authors
- Jang, Chaeyeon; Lee, Ook; Mun, Changbae; Ha, Hyodong
- Issue Date
- Nov-2022
- Publisher
- Little Lion Scientific
- Keywords
- Cases Study; Phishing Attack; Semantic Network Analysis; Text Mining
- Citation
- Journal of Theoretical and Applied Information Technology, v.100, no.22, pp.6758 - 6773
- Indexed
- SCOPUS
- Journal Title
- Journal of Theoretical and Applied Information Technology
- Volume
- 100
- Number
- 22
- Start Page
- 6758
- End Page
- 6773
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/182192
- ISSN
- 1992-8645
- Abstract
- In the modern knowledge and information society, hacking is causing great problems in each area of the industry. Recently, techniques such as distributed denial of service attacks and attacks on management vulnerabilities of cloud servers are gradually evolving. In this study, phishing types were analyzed based on the results of word frequency analysis, clusters were identified, and network analysis was conducted. Through the graph derived from the analysis results, it was possible to identify main keywords, relationships, and trends, and present practical review items for countermeasures against phishing attacks. It also provides a foundation for designing phishing attack prevention measures. By applying this research methodology to the analysis of open source vulnerabilities in the future, it will be possible to have an adaptive defense system for changes in hacking techniques. © 2022 Little Lion Scientific.
- Files in This Item
-
Go to Link
- Appears in
Collections - 서울 공과대학 > 서울 정보시스템학과 > 1. Journal Articles
![qrcode](https://api.qrserver.com/v1/create-qr-code/?size=55x55&data=https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/182192)
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.