Characterizing phishing attacks using natural language processing

Maria Fernanda Cazares, Roberto Andrade, Gustavo Navas, Walter Fuertes, Jhonathan Herrera

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Currently, there are many ways that phishing attacks placed people and businesses at risk. In the economic causes losses the money; in the social aspect, the perception of trust in users decreases; and on the psychological level, fear can avoid the use of digital tools and resources. This study aims to increase efficiency in detecting Phishing attacks using Natural Language Processing (NLP) to explore the mental model people use to detect whether an email is legitimate or not. Specifically, it is based on feedback vectorization and the movement of the mouse, which was obtained when the participants interacted in a test to detect phishing. The results obtained allow us to identify that people based their decision on the URL analysis in the mental model of legitimation and phishing decision. However, in the phishing model, the number of characteristics in each indicator would be more diverse and broader, which produces new challenges and future directions in this solution.

Original languageEnglish
Title of host publicationProceedings of the 2021 5th World Conference on Smart Trends in Systems Security and Sustainability, WorldS4 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages224-229
Number of pages6
ISBN (Electronic)9781665400961
DOIs
StatePublished - 29 Jul 2021
Event5th World Conference on Smart Trends in Systems Security and Sustainability, WorldS4 2021 - London, United Kingdom
Duration: 29 Jul 202130 Jul 2021

Publication series

NameProceedings of the 2021 5th World Conference on Smart Trends in Systems Security and Sustainability, WorldS4 2021

Conference

Conference5th World Conference on Smart Trends in Systems Security and Sustainability, WorldS4 2021
Country/TerritoryUnited Kingdom
CityLondon
Period29/07/2130/07/21

Bibliographical note

Funding Information:
ACKNOWLEDGMENTS We want to thank the resources granted for developing the research project entitled “Detection and Mitigation of Social Engineering attacks applying Cognitive Security, Code: PIC- ESPE-2020-Social Engineering. Likewise, we would like to thank the financial resources provided by the Universidad Politécnica Salesiana of Quito, Ecuador.

Publisher Copyright:
© 2021 IEEE.

Keywords

  • Mental model
  • Natural language processing
  • Phishing

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