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A survey of human-computer interaction (HCI) & natural habits-based behavioural biometric modalities for user recognition schemes
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Gupta, Sandeep, Maple, Carsten, Crispo, Bruno, Raja, Kiran, Yautsiukhin, Artsiom and Martinelli, Fabio (2023) A survey of human-computer interaction (HCI) & natural habits-based behavioural biometric modalities for user recognition schemes. Pattern Recognition, 139 . 109453. doi:10.1016/j.patcog.2023.109453 ISSN 0031-3203.
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Official URL: http://doi.org/10.1016/j.patcog.2023.109453
Abstract
The proliferation of Internet of Things (IoT) systems is having a profound impact across all aspects of life. Recognising and identifying particular users is central to delivering the personalised experience that citizens want to experience, and that organisations wish to deliver. This article presents a survey of human-computer interaction-based (HCI-based) and natural habits-based behavioural biometrics that can be acquired unobtrusively through smart devices or IoT sensors for user recognition purposes. Robust and usable user recognition is also a security requirement for emerging IoT ecosystems to protect them from adversaries. Typically, it can be specified as a fundamental building block for most types of human-to-things accountability principles and access-control methods. However, end-users are facing numerous security and usability challenges in using currently available knowledge- and token-based recognition (i.e., authentication and identification) schemes. To address the limitations of conventional recognition schemes, biometrics, naturally come as a first choice to supporting sophisticated user recognition solutions. We perform a comprehensive review of touch-stroke, swipe, touch signature, hand-movements, voice, gait and footstep behavioural biometrics modalities. This survey analyzes the recent state-of-the-art research of these behavioural biometrics with a goal to identify their attributes and features for generating unique identification signatures. Finally, we present security, privacy, and usability evaluations that can strengthen the designing of robust and usable user recognition schemes for IoT applications.
Item Type: | Journal Article | ||||||||
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Divisions: | Faculty of Science, Engineering and Medicine > Engineering > WMG (Formerly the Warwick Manufacturing Group) | ||||||||
Journal or Publication Title: | Pattern Recognition | ||||||||
Publisher: | Pergamon | ||||||||
ISSN: | 0031-3203 | ||||||||
Official Date: | July 2023 | ||||||||
Dates: |
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Volume: | 139 | ||||||||
Article Number: | 109453 | ||||||||
DOI: | 10.1016/j.patcog.2023.109453 | ||||||||
Status: | Peer Reviewed | ||||||||
Publication Status: | Published | ||||||||
Access rights to Published version: | Restricted or Subscription Access |
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