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AN ANALYSIS OF PHISHING CASES USING TEXT MINING

Authors
Jang, ChaeyeonLee, OokMun, ChangbaeHa, 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.
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