research-article

How Unique do we Move? Understanding the Human Body and Context Factors for User Identification

Authors:

Yasmeen Abdrabou,

Quy Dat Nguyen,

Ken PfeufferAuthors Info & Claims

MuC '23: Proceedings of Mensch und Computer 2023

Pages 127 - 137

https://doi.org/10.1145/3603555.3603574

Published: 03 September 2023 Publication History

Abstract

Past work showed great promise in biometric user identification and authentication through exploiting specific features of specific body parts. We investigate human motion across the whole body, to explore what parts of the body exhibit more unique movement patterns, and are more suitable to identify users in general. We collect and analyze full-body motion data across various activities (e.g., sitting, standing), handheld objects (uni- or bimanual), and tasks (e.g., watching TV or walking). Our analysis shows, e.g., that gait as a strong feature amplifies when carrying items, game activity elicits more unique behaviors than texting on a smartphone, and motion features are robust across body parts whereas posture features are more robust across tasks. Our work provides a holistic reference on how context affects human motion to identify us across a variety of factors, useful to inform researchers and practitioners of behavioral biometric systems on a large scale.

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Cited By

Liebers JLaskowski PRademaker FSabel LHoppen JGruenefeld USchneegass S(2024)Kinetic Signatures: A Systematic Investigation of Movement-Based User Identification in Virtual RealityProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642471(1-19)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642471
Rack CNair VSchach LFoschum FRoth MLatoschik M(2024)Navigating the Kinematic Maze: Analyzing, Standardizing and Unifying XR Motion Datasets2024 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW)10.1109/VRW62533.2024.00098(507-514)Online publication date: 16-Mar-2024
https://doi.org/10.1109/VRW62533.2024.00098

Index Terms

How Unique do we Move? Understanding the Human Body and Context Factors for User Identification
1. Security and privacy
  1. Human and societal aspects of security and privacy

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cover image ACM Other conferences

MuC '23: Proceedings of Mensch und Computer 2023

September 2023

593 pages

ISBN:9798400707711

DOI:10.1145/3603555

Copyright © 2023 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Published: 03 September 2023

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MuC '23: Mensch und Computer 2023

September 3 - 6, 2023

Rapperswil, Switzerland

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Cited By

Liebers JLaskowski PRademaker FSabel LHoppen JGruenefeld USchneegass S(2024)Kinetic Signatures: A Systematic Investigation of Movement-Based User Identification in Virtual RealityProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642471(1-19)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642471
Rack CNair VSchach LFoschum FRoth MLatoschik M(2024)Navigating the Kinematic Maze: Analyzing, Standardizing and Unifying XR Motion Datasets2024 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW)10.1109/VRW62533.2024.00098(507-514)Online publication date: 16-Mar-2024
https://doi.org/10.1109/VRW62533.2024.00098

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