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Human-Generated and Machine-Generated Ratings of Password Strength: What Do Users Trust More?

Alqahtani, Saeed Ibrahim, Li, Shujun, Yuan, Haiyue, Rusconi, Patrice (2020) Human-Generated and Machine-Generated Ratings of Password Strength: What Do Users Trust More? EAI Endorsed Transactions on Security and Safety, 18 (e1). ISSN 2032-9393. (doi:10.4108/eai.13-7-2018.162797) (KAR id:79945)

Abstract

Proactive password checkers have been widely used to persuade users to select stronger passwords by providing machine-generated strength ratings of passwords. If such ratings do not match human-generated ratings of human users, there can be a loss of trust in PPCs. In order to study the effectiveness of PPCs, it would be useful to investigate how human users perceive such machine- and human-generated ratings in terms of their trust, which has been rarely studied in the literature. To fill this gap, we report a large-scale crowdsourcing study with over 1,000 workers. The participants were asked to choose which of the two ratings they trusted more. The passwords were selected based on a survey of over 100 human password experts. The results revealed that participants exhibited four distinct behavioral patterns when the passwords were hidden, and many changed their behaviors significantly after the passwords were disclosed, suggesting their reported trust was influenced by their own judgments.

Item Type: Article
DOI/Identification number: 10.4108/eai.13-7-2018.162797
Projects: [UNSPECIFIED] COMMANDO-HUMANS: COMputational modeling and Automatic Non-intrusive Detection Of HUMan behAviourbased iNSecurity
Uncontrolled keywords: Password strength, password meter, user perception, trust, human-generated, machine-generated, ratings
Subjects: B Philosophy. Psychology. Religion > BF Psychology
Q Science > QA Mathematics (inc Computing science) > QA 75 Electronic computers. Computer science
Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming, > QA76.9.H85 Human computer interaction
Divisions: Faculties > University wide - Teaching/Research Groups > Centre for Cyber Security Research
Faculties > Sciences > School of Computing
Faculties > Sciences > School of Computing > Security Group
Depositing User: Shujun Li
Date Deposited: 04 Feb 2020 19:32 UTC
Last Modified: 05 Feb 2020 08:50 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/79945 (The current URI for this page, for reference purposes)
Li, Shujun: https://orcid.org/0000-0001-5628-7328
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