Analysis of phishing emails

被引:0
|
作者
Burita L. [1 ]
Matoulek P. [1 ]
Halouzka K. [1 ]
Kozak P. [1 ]
机构
[1] Department of Informatics and Cyber Operations, University of Defence, 65 Kounicova Street, Brno
来源
Burita, Ladislav (ladislav.burita@unob.cz) | 1600年 / American Institute of Mathematical Sciences卷 / 05期
关键词
Charity; Fund; Others); Phishing email; analysis; statistics; segmentation (business; Text analytical SW Tovek; Transfer;
D O I
10.3934/ELECTRENG.2021006
中图分类号
学科分类号
摘要
This research aims to describe and analyze phishing emails. The problem of phishing, types of message content of phishing emails, and the basic techniques of phishing email attacks are explained by way of introduction. The study also includes a review of the relevant literature on Web of Science and analyzes articles that deal with the threat of phishing attacks and defense against them. Data collected within a time interval of two months from two email accounts of one of the authors of the study was used for the analysis of 200 email messages. Data has been resented in tabular form, to allow further statistical processing using functions such as sum, average and frequency analysis. The core part of the study involved the classification and segmentation of emails according to the main goals of the sent message. The text analytical software Tovek, was used for the analysis, Contribution of the manuscript is in the understanding of phishing emails and extending the knowledge base in education and training in phishing email defense. The discussion compares the results of this research with those of the studies mentioned in the ―Introduction" and ―Literature review" sections. Furthermore, the emerging problems and limitations of the use of text analytical software are described, and finally the issue is devoted to problems with obtaining personal data from recipients’ emails. The ―Conclusion" section summarizes the contributions of this research. © 2021 the Author(s)
引用
收藏
页码:93 / 116
页数:23
相关论文
共 50 条
  • [31] A cognitive approach to the decision to trust or distrust phishing emails
    Arduin, Pierre-Emmanuel
    INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH, 2023, 30 (03) : 1263 - 1298
  • [32] The Influence of Human Factors on the Intention to Report Phishing Emails
    Marin, Ioana
    Burda, Pavlo
    Allodi, Luca
    Zannone, Nicola
    PROCEEDINGS OF THE 2023 CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS, CHI 2023, 2023,
  • [33] Better beware: comparing metacognition for phishing and legitimate emails
    Canfield, Casey Inez
    Fischhoff, Baruch
    Davis, Alex
    METACOGNITION AND LEARNING, 2019, 14 (03) : 343 - 362
  • [34] Verbal Deception Cue Training for the Detection of Phishing Emails
    Lim, Jaewan
    Zhou, Lina
    Zhang, Dongsong
    2021 IEEE INTERNATIONAL CONFERENCE ON INTELLIGENCE AND SECURITY INFORMATICS (ISI), 2021, : 103 - 105
  • [35] A method to Measure the Efficiency of Phishing Emails Detection Features
    Al-Daeef, Melad Mohamed
    Basir, Nurlida
    Saudi, Madihah Mohd
    2014 INTERNATIONAL CONFERENCE ON INFORMATION SCIENCE AND APPLICATIONS (ICISA), 2014,
  • [36] Why they ignore English Emails: The challenges of non-native speakers in identifying phishing emails
    Hasegawa, Ayako A.
    Yamashita, Naomi
    Akiyama, Mitsuaki
    Mori, Tatsuya
    Proceedings of the 17th Symposium on Usable Privacy and Security, SOUPS 2021, 2021, : 319 - 338
  • [37] Phishing Email: Could We Get Rid of It? A Review on Solutions to Combat Phishing Emails
    Ali, Ghassan Ahmed
    EMERGING TRENDS IN INTELLIGENT COMPUTING AND INFORMATICS: DATA SCIENCE, INTELLIGENT INFORMATION SYSTEMS AND SMART COMPUTING, 2020, 1073 : 849 - 856
  • [38] Why do users not report spear phishing emails?
    Kwak, Youngsun
    Lee, Seyoung
    Damiano, Amanda
    Vishwanath, Arun
    TELEMATICS AND INFORMATICS, 2020, 48 (48)
  • [39] Detection of Phishing Emails using Data Mining Algorithms
    Smadi, Sami
    Aslam, Nauman
    Zhang, Li
    Alasem, Rafe
    Hossain, M. A.
    2015 9TH INTERNATIONAL CONFERENCE ON SOFTWARE, KNOWLEDGE, INFORMATION MANAGEMENT AND APPLICATIONS (SKIMA), 2015,
  • [40] Comparing Machine and Human Ability to Detect Phishing Emails
    Park, Gilchan
    Stuart, Lauren M.
    Taylor, Julia M.
    Raskin, Victor
    2014 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN AND CYBERNETICS (SMC), 2014, : 2322 - 2327