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Title: When Scents Help Me Remember My Password
Authors: Alkasasbeh, AA
Spyridonis, F
Ghinea, G
Keywords: olfactory media;authentication;olfactory passwords;information recall;QoE
Issue Date: 20-Aug-2021
Publisher: Association for Computing Machinery (ACM)
Citation: Anas Ali Alkasasbeh, et al. (2021) When Scents Help Me Remember My Password. ACM Trans. Appl. 18 (3), pp. 1 - 18.,
Abstract: Current authentication processes overwhelmingly rely on audiovisual data, comprising images, text or audio. However, the use of olfactory data (scents) has remained unexploited in the authentication process, notwithstanding their verified potential to act as cues for information recall. Accordingly, in this paper, a new authentication process is proposed in which olfactory media are used as cues in the login phase. To this end, PassSmell, a proof of concept authentication application, is developed in which words and olfactory media act as passwords and olfactory passwords, respectively. In order to evaluate the potential of PassSmell, two different versions were developed, namely one which was olfactory-enhanced and another which did not employ olfactory media. Forty-two participants were invited to take part in the experiment, evenly split into a control and experimental group. For assessment purposes, we recorded the time taken to logon as well as the number of failed/successful login attempts; we also asked users to complete a Quality of Experience (QoE) questionnaire. In terms of time taken, a significant difference was found between the experimental and the control groups, as determined by an independent sample t-test. Similar results were found with respect to average scores and the number of successful attempts. Regarding user QoE, having olfactory media with words influenced the users positively, emphasizing the potential of using this kind of authentication application in the future.
Description: Publisher version is definitive and accessible via DOI | The full text file is the author version
ISSN: 1544-3558
Appears in Collections:Dept of Computer Science Research Papers

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