Motion Passwords
Authors: 
Christian Rack, Lukas Schach, Felix Achter, Yousof Shehada, Jinghuai Lin, 
Marc Erich LatoschikAuthors Info & Claims
Christian Rack, Lukas Schach, Felix Achter, Yousof Shehada, Jinghuai Lin, Marc Erich LatoschikAuthors Info & ClaimsArticle No.: 19, Pages 1 - 11
Abstract
This paper introduces “Motion Passwords”, a novel biometric authentication approach where virtual reality users verify their identity by physically writing a chosen word in the air with their hand controller. This method allows combining three layers of verification: knowledge-based password input, handwriting style analysis, and motion profile recognition. As a first step towards realizing this potential, we focus on verifying users based on their motion profiles. We conducted a data collection study with 48 participants, who performed over 3800 Motion Password signatures across two sessions. We assessed the effectiveness of feature-distance and similarity-learning methods for motion-based verification using the Motion Passwords as well as specific and uniform ball-throwing signatures used in previous works. In our results, the similarity-learning model was able to verify users with the same accuracy for both signature types. This demonstrates that Motion Passwords, even when applying only the motion-based verification layer, achieve reliability comparable to previous methods. This highlights the potential for Motion Passwords to become even more reliable with the addition of knowledge-based and handwriting style verification layers. Furthermore, we present a proof-of-concept Unity application demonstrating the registration and verification process with our pretrained similarity-learning model. We publish our code, the Motion Password dataset, the pretrained model, and our Unity prototype on https://github.com/cschell/MoPs
References
[1]
Ashwin Ajit, Natasha Kholgade Banerjee, and Sean Banerjee. 2019. Combining Pairwise Feature Matches from Device Trajectories for Biometric Authentication in Virtual Reality Environments. In 2019 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR). IEEE, 9–16. https://doi.org/10.1109/AIVR46125.2019.00012
[2]
Thomas M. Breuel. 2008. The OCRopus Open Source OCR System. In Document Recognition and Retrieval XV, Berrin A. Yanikoglu and Kathrin Berkner (Eds.). Vol. 6815. SPIE / International Society for Optics and Photonics, 68150F. https://doi.org/10.1117/12.783598
[3]
Moises Diaz, Miguel A. Ferrer, Donato Impedovo, Muhammad Imran Malik, Giuseppe Pirlo, and Réjean Plamondon. 2019. A Perspective Analysis of Handwritten Signature Technology. Acm Computing Surveys 51, 6, Article 117 (Jan. 2019). https://doi.org/10.1145/3274658
[4]
Tafadzwa Joseph Dube and Ahmed Sabbir Arif. 2019. Text Entry in Virtual Reality: A Comprehensive Review of the Literature. In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 11567 LNCS. Springer International Publishing, Cham, 419–437. https://doi.org/10.1007/978-3-030-22643-5_33/TABLES/5
[5]
M.C. Fairhurst and E. Kaplani. 2003. Perceptual Analysis of Handwritten Signatures for Biometric Authentication. IEE Proceedings - Vision, Image, and Signal Processing 150, 6 (2003), 389. https://doi.org/10.1049/ip-vis:20031046
[6]
William Falcon, Jirka Borovec, Adrian Wälchli, Nic Eggert, Justus Schock, Jeremy Jordan, Nicki Skafte, Ir1dXD, Vadim Bereznyuk, Ethan Harris, Tullie Murrell, Peter Yu, Sebastian Præsius, Travis Addair, Jacob Zhong, Dmitry Lipin, So Uchida, Shreyas Bapat, Hendrik Schröter, Boris Dayma, Alexey Karnachev, Akshay Kulkarni, Shunta Komatsu, Martin.B, Jean-Baptiste SCHIRATTI, Hadrien Mary, Donal Byrne, Cristobal Eyzaguirre, Cinjon, and Anton Bakhtin. 2020. PyTorchLightning/Pytorch-Lightning: 0.7.6 Release. Zenodo. https://doi.org/10.5281/ZENODO.3828935
[7]
Anil K. Jain, Arun A. Ross, and Karthik Nandakumar. 2011. Introduction to Biometrics. Springer US. https://doi.org/10.1007/978-0-387-77326-1
[8]
Eakta Jain, Lisa Anthony, Aishat Aloba, Amanda Castonguay, Isabella Cuba, Alex Shaw, and Julia Woodward. 2016. Is the Motion of a Child Perceivably Different from the Motion of an Adult?ACM Transactions on Applied Perception 13, 4 (July 2016), 1–17. https://doi.org/10.1145/2947616
[9]
Jiajia Jiang, Songxuan Lai, Lianwen Jin, and Yecheng Zhu. 2022. DsDTW: Local Representation Learning with Deep Soft-DTW for Dynamic Signature Verification. IEEE Transactions on Information Forensics and Security 17 (2022), 2198–2212. https://doi.org/10.1109/TIFS.2022.3180219
[10]
Florian Kern, Peter Kullmann, Elisabeth Ganal, Kristof Korwisi, René Stingl, Florian Niebling, and Marc Erich Latoschik. 2021. Off-The-Shelf Stylus: Using XR Devices for Handwriting and Sketching on Physically Aligned Virtual Surfaces. Frontiers in Virtual Reality 2 (June 2021). https://doi.org/10.3389/frvir.2021.684498
[11]
Florian Kern, Jonathan Tschanter, and Marc Erich Latoschik. 2024. Handwriting for Text Input and the Impact of XR Displays, Surface Alignments, and Sentence Complexities. IEEE Transactions on Visualization and Computer Graphics 30, 5 (2024), 2357–2367. https://doi.org/10.1109/TVCG.2024.3372124
[12]
Salman H. Khan, Zeashan Khan, and Faisal Shafait. 2013. Can Signature Biometrics Address Both Identification and Verification Problems?. In 2013 12th International Conference on Document Analysis and Recognition. 981–985. https://doi.org/10.1109/ICDAR.2013.198
[13]
Benjamin Kiessling. 2019. Kraken - a Universal Text Recognizer for the Humanities. https://doi.org/10.34894/Z9G2EX
[14]
Pascal Knierim, Valentin Schwind, Anna Maria Feit, Florian Nieuwenhuizen, and Niels Henze. 2018. Physical Keyboards in Virtual Reality: Analysis of Typing Performance and Effects of Avatar Hands. In Conference on Human Factors in Computing Systems - Proceedings, Vol. 2018-April. Association for Computing Machinery, New York, NY, USA. https://doi.org/10.1145/3173574.3173919
[15]
Alexander Kupin, Benjamin Moeller, Yijun Jiang, Natasha Kholgade Banerjee, and Sean Banerjee. 2019. Task-Driven Biometric Authentication of Users in Virtual Reality (VR) Environments. In MultiMedia Modeling, Ioannis Kompatsiaris, Benoit Huet, Vasileios Mezaris, Cathal Gurrin, Wen-Huang Cheng, and Stefanos Vrochidis (Eds.). Springer International Publishing, Cham, 55–67.
[16]
Sugang Li, Ashwin Ashok, Yanyong Zhang, Chenren Xu, Janne Lindqvist, and Macro Gruteser. 2016. Whose Move Is It Anyway? Authenticating Smart Wearable Devices Using Unique Head Movement Patterns. 2016 IEEE International Conference on Pervasive Computing and Communications, PerCom 2016 (2016), 1–9. https://doi.org/10.1109/PERCOM.2016.7456514
[17]
Jonathan Liebers, Mark Abdelaziz, and Lukas Mecke. 2021. Understanding User Identification in Virtual Reality through Behavioral Biometrics and the Effect of Body Normalization. In Conference on Human Factors in Computing Systems - Proceedings. Association for Computing Machinery, New York, NY, USA, 1–11. https://doi.org/10.1145/3411764.3445528
[18]
Duo Lu, Yuli Deng, and Dijiang Huang. 2021. Global Feature Analysis and Comparative Evaluation of Freestyle In-Air-Handwriting Passcode for User Authentication. In Annual Computer Security Applications Conference. ACM, Virtual Event USA, 468–481. https://doi.org/10.1145/3485832.3485906
[19]
Mark Roman Miller, Fernanda Herrera, Hanseul Jun, James A. Landay, and Jeremy N. Bailenson. 2020. Personal Identifiability of User Tracking Data during Observation of 360-Degree VR Video. Scientific Reports 10, 1 (2020), 1–10. https://doi.org/10.1038/s41598-020-74486-y
[20]
Robert Miller, Ashwin Ajit, Natasha Kholgade Banerjee, and Sean Banerjee. 2019. Realtime Behavior-Based Continual Authentication of Users in Virtual Reality Environments. In 2019 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR). IEEE, 253–2531. https://doi.org/10.1109/AIVR46125.2019.00058
[21]
Robert Miller, Natasha Kholgade Banerjee, and Sean Banerjee. 2020. Within-System and Cross-System Behavior-Based Biometric Authentication in Virtual Reality. Proceedings - 2020 IEEE Conference on Virtual Reality and 3D User Interfaces, VRW 2020 (2020), 311–316. https://doi.org/10.1109/VRW50115.2020.00070
[22]
Robert Miller, Natasha Kholgade Banerjee, and Sean Banerjee. 2021. Using Siamese Neural Networks to Perform Cross-System Behavioral Authentication in Virtual Reality. In 2021 IEEE Virtual Reality and 3D User Interfaces (VR). IEEE, 140–149. https://doi.org/10.1109/VR50410.2021.00035
[23]
Robert Miller, Natasha Kholgade Banerjee, and Sean Banerjee. 2022. Combining Real-World Constraints on User Behavior with Deep Neural Networks for Virtual Reality (VR) Biometrics. In Proceedings - 2022 IEEE Conference on Virtual Reality and 3D User Interfaces, VR 2022. Institute of Electrical and Electronics Engineers Inc., 409–418. https://doi.org/10.1109/VR51125.2022.00060
[24]
Kevin Musgrave, Serge Belongie, and Ser-Nam Lim. 2020. A Metric Learning Reality Check. In Computer Vision – ECCV 2020, Andrea Vedaldi, Horst Bischof, Thomas Brox, and Jan-Michael Frahm (Eds.). Springer International Publishing, Cham, 681–699.
[25]
Kevin Musgrave, Serge Belongie, and Ser-Nam Lim. 2020. PyTorch Metric Learning. arxiv:2008.09164 [cs]
[26]
Vivek Nair, Wenbo Guo, Justus Mattern, Rui Wang, James F. O’Brien, Louis Rosenberg, and Dawn Song. 2023. Unique Identification of 50,000+ Virtual Reality Users from Head & Hand Motion Data. (Feb. 2023).
[27]
Vivek Nair, Louis Rosenberg, James F. O’Brien, and Dawn Song. 2023. Truth in Motion: The Unprecedented Risks and Opportunities of Extended Reality Motion Data. (2023). https://doi.org/10.48550/ARXIV.2306.06459
[28]
Ken Pfeuffer, Matthias J. Geiger, Sarah Prange, Lukas Mecke, Daniel Buschek, and Florian Alt. 2019. Behavioural Biometrics in VR: Identifying People from Body Motion and Relations in Virtual Reality. In 2019 CHI Conference on Human Factors in Computing Systems - CHI ’19, Vol. 12. Association for Computing Machinery, New York, NY, USA, 1–12.
[29]
S. Prabhakar, S. Pankanti, and A.K. Jain. 2003. Biometric Recognition: Security and Privacy Concerns. IEEE Security & Privacy 1, 2 (2003), 33–42. https://doi.org/10.1109/MSECP.2003.1193209
[30]
Christian Rack, Tamara Fernando, Murat Yalcin, Andreas Hotho, and Marc Erich Latoschik. 2023. Who Is Alyx? A New Behavioral Biometric Dataset for User Identification in XR. Frontiers in Virtual Reality 4 (2023). https://doi.org/10.3389/frvir.2023.1272234
[31]
Christian Rack, Andreas Hotho, and Marc Erich Latoschik. 2022. Comparison of Data Encodings and Machine Learning Architectures for User Identification on Arbitrary Motion Sequences. In 2022 IEEE International Conference on Artificial Intelligence and Virtual Reality, AIVR 2022. IEEE.
[32]
Christian Rack, Konstantin Kobs, Tamara Fernando, Andreas Hotho, and Marc Erich Latoschik. 2023. Versatile User Identification in Extended Reality Using Pretrained Similarity-Learning. arxiv:2302.07517 [cs]
[33]
Christian Rack, Vivek Nair, Lukas Schach, Felix Foschum, Marcel Roth, and Marc Erich Latoschik. 2024. Navigating the Kinematic Maze: Analyzing, Standardizing and Unifying XR Motion Datasets. In 2024 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW). IEEE.
[34]
Cynthia E. Rogers, Alexander W. Witt, Alexander D. Solomon, and Krishna K. Venkatasubramanian. 2015. An Approach for User Identification for Head-Mounted Displays. ISWC 2015 - Proceedings of the 2015 ACM International Symposium on Wearable Computers (2015), 143–146. https://doi.org/10.1145/2802083.2808391
[35]
Osvaldo A. Rosso, Raydonal Ospina, and Alejandro C. Frery. 2016. Classification and Verification of Handwritten Signatures with Time Causal Information Theory Quantifiers. PLOS ONE 11, 12 (Dec. 2016), 1–19. https://doi.org/10.1371/journal.pone.0166868
[36]
H. Sakoe and S. Chiba. 1978. Dynamic Programming Algorithm Optimization for Spoken Word Recognition. IEEE Transactions on Acoustics, Speech, and Signal Processing 26, 1 (1978), 43–49. https://doi.org/10.1109/TASSP.1978.1163055
[37]
Ray Smith. 2007. An Overview of the Tesseract OCR Engine. In ICDAR ’07: Proceedings of the Ninth International Conference on Document Analysis and Recognition. IEEE Computer Society, Washington, DC, USA, 629–633.
[38]
Sophie Stephenson, Bijeeta Pal, Stephen Fan, Earlence Fernandes, Yuhang Zhao, and Rahul Chatterjee. 2022. SoK: Authentication in Augmented and Virtual Reality. In 2022 IEEE Symposium on Security and Privacy (SP). IEEE, 267–284. https://doi.org/10.1109/SP46214.2022.9833742
[39]
Romain Tavenard, Johann Faouzi, Gilles Vandewiele, Felix Divo, Guillaume Androz, Chester Holtz, Marie Payne, Roman Yurchak, Marc Rußwurm, Kushal Kolar, and Eli Woods. 2020. Tslearn, a Machine Learning Toolkit for Time Series Data. Journal of Machine Learning Research 21, 118 (2020), 1–6.
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October 2024
633 pages
ISBN:9798400705359
DOI:10.1145/3641825
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Published: 09 October 2024
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VRST '24: 30th ACM Symposium on Virtual Reality Software and Technology
October 9 - 11, 2024
Trier, Germany
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