Facelock : familiarity-based graphical authentication

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Jenkins, Rob and McLachlan, Jane L. and Renaud, Karen (2014) Facelock : familiarity-based graphical authentication. PeerJ, 2 (e444). ISSN 2167-8359 (https://doi.org/10.7717/peerj.444)

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Abstract

Authentication codes such as passwords and PIN numbers are widely used to control access to resources. One major drawback of these codes is that they are difficult to remember. Account holders are often faced with a choice between forgetting a code, which can be inconvenient, or writing it down, which compromises security. In two studies, we test a new knowledge-based authentication method that does not impose memory load on the user. Psychological research on face recognition has revealed an important distinction between familiar and unfamiliar face perception: When a face is familiar to the observer, it can be identified across a wide range of images. However, when the face is unfamiliar, generalisation across images is poor. This contrast can be used as the basis for a personalised ‘facelock’, in which authentication succeeds or fails based on image-invariant recognition of faces that are familiar to the account holder. In Study 1, account holders authenticated easily by detecting familiar targets among other faces (97.5% success rate), even after a one-year delay (86.1% success rate). Zero-acquaintance attackers were reduced to guessing (

ORCID iDs

Jenkins, Rob, McLachlan, Jane L. and Renaud, Karen ORCID logoORCID: https://orcid.org/0000-0002-7187-6531;
  • Item type:Article
    ID code:82749
    Dates:
    Date
    Event
    24 June 2014
    Published
    2 June 2014
    Accepted
    Notes:July 4, 2014: (Minor Correction): The bottom right panel of Figure 2 was not correctly attributed to the original photographer or reproduced under the correct distribution license. This panel is an extract from an image owned by Professor Eszter Hargittai and should have been reproduced (without alteration) under a Creative Commons “BY NC ND 2.0” license (the original image can be viewed at https://www.flickr.com/photos/eszter/161240402/in/set-7215760379).
    Subjects:Science > Mathematics > Electronic computers. Computer science
    Department:Faculty of Science > Computer and Information Sciences
    Depositing user: Pure Administrator
    Date deposited:13 Oct 2022 12:25
    Last modified:11 Nov 2024 13:38
    URI:https://strathprints.strath.ac.uk/id/eprint/82749
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