A survey of human-computer interaction (HCI) & natural habits-based behavioural biometric modalities for user recognition schemes

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. Ro-bust 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 nu-merous security and usability challenges in using currently available knowledge-and token-based recog-nition (i.e., authentication and identification ) schemes. To address the limitations of conventional recog-nition 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 gener-ating 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.(c) 2023 Elsevier Ltd. All rights reserved.

Automated summary

This article presents a survey on HCI-based and natural habits-based behavioural biometrics for user recognition in IoT systems. Robust and usable user recognition is crucial for the security of emerging IoT ecosystems. Biometrics provide a solution to the limitations of conventional recognition schemes, and this article reviews the state-of-the-art research on touch-stroke, swipe, touch signature, hand-movements, voice, gait, and footstep behavioural biometrics modalities. The article also explores the security, privacy, and usability evaluations to enhance the design of user recognition schemes for IoT applications.