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Comparison of different training methods impact on users ability to detect phishing

SND-ID: 2021-339

Creator/Principal investigator(s)

Joakim Kävrestad - University of Skövde

Description

The data was collected in a simulated experiment with the purpose of studying how different types of cybersecurity training impacts users' ability to correctly identify phishing e-mail. For the experiment, an isolated e-mail world was developed and participants were given an inbox containing 5 legitimate e-mails and 6 phishing e-mails. They were asked to assume the persona of the inbox owner and then delete all e-mails they considered to be phishing. They were also asked to “think aloud” during the experiment. Their performance was monitored by an experiment supervisor using an eye tracker and continuous monitoring of the participants screen.

Language

English

Research principal, contributors, and funding

Research principal

University of Skövde

Responsible department/unit

School of Informatics

Contributor(s)

Marcus Nohlberg - University of Skövde

Funding

  • Funding agency: The Swedish Post and Telecom Authority
  • Funding agency's reference number: 19-10617
  • Project name on the application: Utveckling av beslutsstöd för användare i riskfyllda situationer online (UBARSO)
Protection and ethical review

Data contains personal data

No

Method and time period

Unit of analysis

Study design

Randomised controlled trial (RCT)

Geographic coverage
Topic and keywords

Research area

Computer Science, Information Systems (The Swedish standard of fields of research 2011)
OTHER (CESSDA Topic Classification)

Keywords

cybersecurity, användarträning, cybersäkerhetsträning, phishing

Publications
Dataset
Comparison of different training methods impact on users ability to detect phishing

Download data

data.xlsx (15.28 KB)

Associated documentation

Version 1

Citation

Joakim Kävrestad. University of Skövde (2022). Comparison of different training methods impact on users ability to detect phishing. Swedish National Data Service. Version 1. https://doi.org/10.5878/g6d9-7210

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Data format / data structure

Numeric

Creator/Principal investigator(s)

Joakim Kävrestad - University of Skövde

License

Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
Published: 2022-02-18