The human factor in phishing: Collecting and analyzing user behavior when reading emails

Author:

Gallo LuigiORCID,Gentile DaniloORCID,Ruggiero Saverio,Botta AlessioORCID,Ventre Giorgio

Funder

European Commission

Cisco Systems

Università degli Studi di Napoli Federico II

Publisher

Elsevier BV

Subject

Law,General Computer Science

Reference45 articles.

1. Applying machine learning and natural language processing to detect phishing email;Alhogail;Comput. Secur.,2021

2. The need for new antiphishing measures against spear-phishing attacks;Allodi;IEEE Secur. Priv.,2019

3. Phishing iq tests measure fear, not ability;Anandpara,2007

4. A novel method of spam mail detection using text based clustering approach;Basavaraju;Int. J. Comput. Appl.,2010

5. A survey of learning-based techniques of email spam filtering;Blanzieri;Artif. Intell. Rev.,2008

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1. Effects of visual risk indicators on phishing detection behavior: An eye-tracking experiment;Computers & Security;2024-09

2. Where Do Users Look When Deciding If a Text Message is Safe or Malicious?;Proceedings of the Human Factors and Ergonomics Society Annual Meeting;2024-08-12

3. Work in Progress: Implicit Association Tests for Understanding Human Factor in Phishing Beyond Awareness;2024 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW);2024-07-08

4. A Gaze-Based Analysis of Human Detection of Email Phishing;2024 Silicon Valley Cybersecurity Conference (SVCC);2024-06-17

5. Exploring GRU-based approaches with attention mechanisms for accurate phishing URL detection;Intelligent Decision Technologies;2024-06-07

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