“Alexa, What’s a Phishing Email?”: Training users to spot phishing emails using a voice assistant
This paper reports the findings from an empirical study investigating the effectiveness of using intelligent voice assistants, Amazon Alexa in our case, to deliver a phishing training to users. Because intelligent voice assistants can hardly utilize visual cues but provide for convenient interaction...
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| Veröffentlicht in: | EURASIP Journal on Information Security Jg. 2022; H. 1; S. 7 - 13 |
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| Hauptverfasser: | , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
Cham
Springer International Publishing
22.11.2022
Springer Nature B.V SpringerOpen |
| Schlagworte: | |
| ISSN: | 2510-523X, 1687-4161, 2510-523X, 1687-417X |
| Online-Zugang: | Volltext |
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| Zusammenfassung: | This paper reports the findings from an empirical study investigating the effectiveness of using intelligent voice assistants, Amazon Alexa in our case, to deliver a phishing training to users. Because intelligent voice assistants can hardly utilize visual cues but provide for convenient interaction with users, we developed an
interaction-based phishing training
focused on the principles of persuasion with examples on how to look for them in phishing emails. To test the effectiveness of this training, we conducted a between-subject study where 120 participants were randomly assigned in three groups: no training, interaction-based training with Alexa, and a facts-and-advice training and assessed a vignette of 28 emails. The results show that the participants in the interaction-based group statistically outperformed the others when detecting phishing emails that employed the following persuasion principles (and/or combinations of): authority, authority/scarcity, commitment, commitment/liking, and scarcity/liking. The paper discusses the implication of this result for future phishing training and anti-phishing efforts. |
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| Bibliographie: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
| ISSN: | 2510-523X 1687-4161 2510-523X 1687-417X |
| DOI: | 10.1186/s13635-022-00133-w |