Slide
Centre Interdisciplinaire
de Recherche et d’Innovation
en Cybersécurité et Société
de Recherche et d’Innovation
en Cybersécurité et Société
1.
Dang, L. B.; Truong, V. Tuan; Le, L. B.; Falk, T. H.
EM-Auth: A Generalizable Eye-Movement Authentication Framework using Event Cameras Proceedings Article
In: IEEE Conf. Artif. Intell., CAI, pp. 2064–2069, Institute of Electrical and Electronics Engineers Inc., 2026, ISBN: 979-833156039-3 (ISBN), (Journal Abbreviation: IEEE Conf. Artif. Intell., CAI).
Abstract | Links | BibTeX | Tags: augmented reality, Authentication, Cameras, Convolutional neural networks, Data privacy, Eye movement patterns, Eye movements, eye tracking, Eye-tracking, Frame-based, High power consumption, Neuromorphic vision sensors, Power potential, Privacy concerns, Temporal resolution, Transfer learning, User authentication, Virtual and augmented reality, virtual reality
@inproceedings{dangEMAuthGeneralizableEyeMovement2026,
title = {EM-Auth: A Generalizable Eye-Movement Authentication Framework using Event Cameras},
author = {L. B. Dang and V. Tuan Truong and L. B. Le and T. H. Falk},
url = {https://www.scopus.com/pages/publications/105042114237?origin=resultslist},
doi = {10.1109/CAI68641.2026.11536355},
isbn = {979-833156039-3 (ISBN)},
year = {2026},
date = {2026-01-01},
booktitle = {IEEE Conf. Artif. Intell., CAI},
pages = {2064–2069},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {With the rapid emergence of virtual and augmented reality (VR/AR) head-mounted devices that closely interact with users' eyes, eye-tracking-based applications are becoming increasingly promising. Among them, eye movement patterns have emerged as a reliable biometric modality for user authentication. However, existing solutions based on conventional frame-based cameras face significant limitations, including low temporal resolution, high latency, high power consumption, and potential privacy concerns due to the detailed appearance captured around the eyes. To address these challenges, we propose EM-Auth, a novel framework for eye-tracking-based user authentication that leverages event cameras, a type of neuromorphic vision sensor providing asynchronous, high-temporal-resolution data, while preserving user privacy. Our method introduces a two-stage spatiotemporal feature extraction pipeline: first, a lightweight convolutional neural network (CNN) extracts spatial features from event streams; second, a transformer-based module models the temporal dependencies to generate robust eye representations. Extensive experiments show that our framework significantly outperforms existing state-of-the-art (SOTA) methods, achieving 0.008 and 0.015 equal error rates (EERs) on two representative datasets. Notably, EM-Auth demonstrates a strong generalization capability. In a zero-shot setting where the model is trained on a specific dataset and evaluated on previously unseen users, our approach achieves authentication accuracies of 98.4% and 95.9% on the EV-Eye and EBV-Eye datasets, respectively. Under cross-dataset evaluation, our framework achieves an authentication accuracy of nearly 85% without additional fine-tuning, and consistently improves performance through transfer learning. © 2026 IEEE.},
note = {Journal Abbreviation: IEEE Conf. Artif. Intell., CAI},
keywords = {augmented reality, Authentication, Cameras, Convolutional neural networks, Data privacy, Eye movement patterns, Eye movements, eye tracking, Eye-tracking, Frame-based, High power consumption, Neuromorphic vision sensors, Power potential, Privacy concerns, Temporal resolution, Transfer learning, User authentication, Virtual and augmented reality, virtual reality},
pubstate = {published},
tppubtype = {inproceedings}
}
With the rapid emergence of virtual and augmented reality (VR/AR) head-mounted devices that closely interact with users' eyes, eye-tracking-based applications are becoming increasingly promising. Among them, eye movement patterns have emerged as a reliable biometric modality for user authentication. However, existing solutions based on conventional frame-based cameras face significant limitations, including low temporal resolution, high latency, high power consumption, and potential privacy concerns due to the detailed appearance captured around the eyes. To address these challenges, we propose EM-Auth, a novel framework for eye-tracking-based user authentication that leverages event cameras, a type of neuromorphic vision sensor providing asynchronous, high-temporal-resolution data, while preserving user privacy. Our method introduces a two-stage spatiotemporal feature extraction pipeline: first, a lightweight convolutional neural network (CNN) extracts spatial features from event streams; second, a transformer-based module models the temporal dependencies to generate robust eye representations. Extensive experiments show that our framework significantly outperforms existing state-of-the-art (SOTA) methods, achieving 0.008 and 0.015 equal error rates (EERs) on two representative datasets. Notably, EM-Auth demonstrates a strong generalization capability. In a zero-shot setting where the model is trained on a specific dataset and evaluated on previously unseen users, our approach achieves authentication accuracies of 98.4% and 95.9% on the EV-Eye and EBV-Eye datasets, respectively. Under cross-dataset evaluation, our framework achieves an authentication accuracy of nearly 85% without additional fine-tuning, and consistently improves performance through transfer learning. © 2026 IEEE.
2.
Brideau-Duquette, M.; Côté, S. S. -P.; Charbonneau, P.; Renaud, P.
When Sexy Avatars Get Weird: How Brain Asymmetry and Oculomotor Dynamics Navigate the Uncanny Proceedings Article
In: S., Itthipuripat; G.A., Ascoli; A., Li; N., Pat; H., Kuai (Ed.): Lect. Notes Comput. Sci., pp. 121–139, Springer Science and Business Media Deutschland GmbH, 2025, ISBN: 03029743 (ISSN); 978-981963293-0 (ISBN), (Journal Abbreviation: Lect. Notes Comput. Sci.).
Abstract | Links | BibTeX | Tags: Brain, Embodied Computing, Eye-tracking, Gaze behaviours, Human machine interaction, Immersive, Nonlinear index, Psychological effects, regression analysis, Regression modelling, Uncanny, Uncanny valley, Virtual environments, virtual reality
@inproceedings{brideau-duquette_when_2025,
title = {When Sexy Avatars Get Weird: How Brain Asymmetry and Oculomotor Dynamics Navigate the Uncanny},
author = {M. Brideau-Duquette and S. S. -P. Côté and P. Charbonneau and P. Renaud},
editor = {Itthipuripat S. and Ascoli G.A. and Li A. and Pat N. and Kuai H.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105002448490&doi=10.1007%2F978-981-96-3294-7_10&partnerID=40&md5=ced02f5a8061a51f213078ce6d6635f3},
doi = {10.1007/978-981-96-3294-7_10},
isbn = {03029743 (ISSN); 978-981963293-0 (ISBN)},
year = {2025},
date = {2025-01-01},
booktitle = {Lect. Notes Comput. Sci.},
volume = {15541 LNAI},
pages = {121–139},
publisher = {Springer Science and Business Media Deutschland GmbH},
abstract = {This study explores the psychological effects of human-machine interaction, particularly focusing on the phenomenon of the uncanny valley within the context of virtual reality (VR). This study specifically investigates the relationship between oculomotor dynamics, EEG asymmetry, and perceived uncanniness in an immersive setting with a realistic human avatar that can generate uncanny feelings. Participants engaged in a VR scenario designed to optimize their sexual interest. Eye-tracking and EEG data were collected during these interactions to assess the predictors of uncanniness. The final regression model identified significant predictors, including EEG asymmetry in frontal and parietal regions and nonlinear indices of gaze behavior. The findings suggest that the more a participants’ attention was attracted towards specific cues, the higher the uncanniness. The interplay between EEG asymmetries and gaze behavior furthermore indicates that these physiological and behavioral responses are closely linked to the perception of uncanniness, offering insights into how humans interact with increasingly lifelike technologies. These insights contribute to a better understanding of HMI’s potential and may inform the development of more engaging and psychologically attuned virtual content. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.},
note = {Journal Abbreviation: Lect. Notes Comput. Sci.},
keywords = {Brain, Embodied Computing, Eye-tracking, Gaze behaviours, Human machine interaction, Immersive, Nonlinear index, Psychological effects, regression analysis, Regression modelling, Uncanny, Uncanny valley, Virtual environments, virtual reality},
pubstate = {published},
tppubtype = {inproceedings}
}
This study explores the psychological effects of human-machine interaction, particularly focusing on the phenomenon of the uncanny valley within the context of virtual reality (VR). This study specifically investigates the relationship between oculomotor dynamics, EEG asymmetry, and perceived uncanniness in an immersive setting with a realistic human avatar that can generate uncanny feelings. Participants engaged in a VR scenario designed to optimize their sexual interest. Eye-tracking and EEG data were collected during these interactions to assess the predictors of uncanniness. The final regression model identified significant predictors, including EEG asymmetry in frontal and parietal regions and nonlinear indices of gaze behavior. The findings suggest that the more a participants’ attention was attracted towards specific cues, the higher the uncanniness. The interplay between EEG asymmetries and gaze behavior furthermore indicates that these physiological and behavioral responses are closely linked to the perception of uncanniness, offering insights into how humans interact with increasingly lifelike technologies. These insights contribute to a better understanding of HMI’s potential and may inform the development of more engaging and psychologically attuned virtual content. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
3.
Brideau-Duquette, M.; Côté, S. S. -P.; Charbonneau, P.; Renaud, P.
When Sexy Avatars Get Weird: How Brain Asymmetry and Oculomotor Dynamics Navigate the Uncanny Proceedings Article
In: S., Itthipuripat; G.A., Ascoli; A., Li; N., Pat; H., Kuai (Ed.): Lect. Notes Comput. Sci., pp. 121–139, Springer Science and Business Media Deutschland GmbH, 2025, ISBN: 03029743 (ISSN); 978-981963293-0 (ISBN), (Journal Abbreviation: Lect. Notes Comput. Sci.).
Abstract | Links | BibTeX | Tags: Brain, Embodied Computing, Eye-tracking, Gaze behaviours, Human machine interaction, Immersive, Nonlinear index, Psychological effects, regression analysis, Regression modelling, Uncanny, Uncanny valley, Virtual environments, virtual reality
@inproceedings{brideau-duquetteWhenSexyAvatars2025,
title = {When Sexy Avatars Get Weird: How Brain Asymmetry and Oculomotor Dynamics Navigate the Uncanny},
author = {M. Brideau-Duquette and S. S. -P. Côté and P. Charbonneau and P. Renaud},
editor = {Itthipuripat S. and Ascoli G.A. and Li A. and Pat N. and Kuai H.},
url = {https://www.scopus.com/pages/publications/105002448490?origin=resultslist},
doi = {10.1007/978-981-96-3294-7_10},
isbn = {03029743 (ISSN); 978-981963293-0 (ISBN)},
year = {2025},
date = {2025-01-01},
booktitle = {Lect. Notes Comput. Sci.},
volume = {15541 LNAI},
pages = {121–139},
publisher = {Springer Science and Business Media Deutschland GmbH},
abstract = {This study explores the psychological effects of human-machine interaction, particularly focusing on the phenomenon of the uncanny valley within the context of virtual reality (VR). This study specifically investigates the relationship between oculomotor dynamics, EEG asymmetry, and perceived uncanniness in an immersive setting with a realistic human avatar that can generate uncanny feelings. Participants engaged in a VR scenario designed to optimize their sexual interest. Eye-tracking and EEG data were collected during these interactions to assess the predictors of uncanniness. The final regression model identified significant predictors, including EEG asymmetry in frontal and parietal regions and nonlinear indices of gaze behavior. The findings suggest that the more a participants’ attention was attracted towards specific cues, the higher the uncanniness. The interplay between EEG asymmetries and gaze behavior furthermore indicates that these physiological and behavioral responses are closely linked to the perception of uncanniness, offering insights into how humans interact with increasingly lifelike technologies. These insights contribute to a better understanding of HMI’s potential and may inform the development of more engaging and psychologically attuned virtual content. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.},
note = {Journal Abbreviation: Lect. Notes Comput. Sci.},
keywords = {Brain, Embodied Computing, Eye-tracking, Gaze behaviours, Human machine interaction, Immersive, Nonlinear index, Psychological effects, regression analysis, Regression modelling, Uncanny, Uncanny valley, Virtual environments, virtual reality},
pubstate = {published},
tppubtype = {inproceedings}
}
This study explores the psychological effects of human-machine interaction, particularly focusing on the phenomenon of the uncanny valley within the context of virtual reality (VR). This study specifically investigates the relationship between oculomotor dynamics, EEG asymmetry, and perceived uncanniness in an immersive setting with a realistic human avatar that can generate uncanny feelings. Participants engaged in a VR scenario designed to optimize their sexual interest. Eye-tracking and EEG data were collected during these interactions to assess the predictors of uncanniness. The final regression model identified significant predictors, including EEG asymmetry in frontal and parietal regions and nonlinear indices of gaze behavior. The findings suggest that the more a participants’ attention was attracted towards specific cues, the higher the uncanniness. The interplay between EEG asymmetries and gaze behavior furthermore indicates that these physiological and behavioral responses are closely linked to the perception of uncanniness, offering insights into how humans interact with increasingly lifelike technologies. These insights contribute to a better understanding of HMI’s potential and may inform the development of more engaging and psychologically attuned virtual content. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
4.
Brideau-Duquette, M.; Côté, S. S. -P.; Charbonneau, P.; Renaud, P.
When Sexy Avatars Get Weird: How Brain Asymmetry and Oculomotor Dynamics Navigate the Uncanny Proceedings Article
In: S., Itthipuripat; G.A., Ascoli; A., Li; N., Pat; H., Kuai (Ed.): Lect. Notes Comput. Sci., pp. 121–139, Springer Science and Business Media Deutschland GmbH, 2025, ISBN: 03029743 (ISSN); 978-981963293-0 (ISBN).
Abstract | Links | BibTeX | Tags: Brain, Embodied Computing, Eye-tracking, Gaze behaviours, Human machine interaction, Immersive, Nonlinear index, Psychological effects, regression analysis, Regression modelling, Uncanny, Uncanny valley, Virtual environments, virtual reality
@inproceedings{brideau-duquetteWhenSexyAvatars2025a,
title = {When Sexy Avatars Get Weird: How Brain Asymmetry and Oculomotor Dynamics Navigate the Uncanny},
author = {M. Brideau-Duquette and S. S. -P. Côté and P. Charbonneau and P. Renaud},
editor = {Itthipuripat S. and Ascoli G.A. and Li A. and Pat N. and Kuai H.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105002448490&doi=10.1007%2F978-981-96-3294-7_10&partnerID=40&md5=ced02f5a8061a51f213078ce6d6635f3},
doi = {10.1007/978-981-96-3294-7_10},
isbn = {03029743 (ISSN); 978-981963293-0 (ISBN)},
year = {2025},
date = {2025-01-01},
booktitle = {Lect. Notes Comput. Sci.},
volume = {15541 LNAI},
pages = {121–139},
publisher = {Springer Science and Business Media Deutschland GmbH},
abstract = {This study explores the psychological effects of human-machine interaction, particularly focusing on the phenomenon of the uncanny valley within the context of virtual reality (VR). This study specifically investigates the relationship between oculomotor dynamics, EEG asymmetry, and perceived uncanniness in an immersive setting with a realistic human avatar that can generate uncanny feelings. Participants engaged in a VR scenario designed to optimize their sexual interest. Eye-tracking and EEG data were collected during these interactions to assess the predictors of uncanniness. The final regression model identified significant predictors, including EEG asymmetry in frontal and parietal regions and nonlinear indices of gaze behavior. The findings suggest that the more a participants’ attention was attracted towards specific cues, the higher the uncanniness. The interplay between EEG asymmetries and gaze behavior furthermore indicates that these physiological and behavioral responses are closely linked to the perception of uncanniness, offering insights into how humans interact with increasingly lifelike technologies. These insights contribute to a better understanding of HMI’s potential and may inform the development of more engaging and psychologically attuned virtual content. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.},
keywords = {Brain, Embodied Computing, Eye-tracking, Gaze behaviours, Human machine interaction, Immersive, Nonlinear index, Psychological effects, regression analysis, Regression modelling, Uncanny, Uncanny valley, Virtual environments, virtual reality},
pubstate = {published},
tppubtype = {inproceedings}
}
This study explores the psychological effects of human-machine interaction, particularly focusing on the phenomenon of the uncanny valley within the context of virtual reality (VR). This study specifically investigates the relationship between oculomotor dynamics, EEG asymmetry, and perceived uncanniness in an immersive setting with a realistic human avatar that can generate uncanny feelings. Participants engaged in a VR scenario designed to optimize their sexual interest. Eye-tracking and EEG data were collected during these interactions to assess the predictors of uncanniness. The final regression model identified significant predictors, including EEG asymmetry in frontal and parietal regions and nonlinear indices of gaze behavior. The findings suggest that the more a participants’ attention was attracted towards specific cues, the higher the uncanniness. The interplay between EEG asymmetries and gaze behavior furthermore indicates that these physiological and behavioral responses are closely linked to the perception of uncanniness, offering insights into how humans interact with increasingly lifelike technologies. These insights contribute to a better understanding of HMI’s potential and may inform the development of more engaging and psychologically attuned virtual content. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
5.
Boukhalfi, T.; Joyal, C.; Bouchard, S.; Neveu, S. M.; Renaud, P.
Tools and techniques for real-time data acquisition and analysis in brain computer interface studies using qEEG and eye tracking in virtual reality environment Proceedings Article
In: A., Zaremba M. Sasiadek J. Dolgui (Ed.): IFAC-PapersOnLine, pp. 46–51, 2015, ISSN: 24058963, (ISSN: 24058963 Issue: 3).
Abstract | Links | BibTeX | Tags: Acquisition, Analysis, brain computer interface, Data acquisition, Electroencephalography, eye tracking, Eye-tracking, Forensic, Forensic engineering, Heat maps, Interfaces (computer), Psychiatry, Real time, virtual reality
@inproceedings{boukhalfi_tools_2015,
title = {Tools and techniques for real-time data acquisition and analysis in brain computer interface studies using qEEG and eye tracking in virtual reality environment},
author = {T. Boukhalfi and C. Joyal and S. Bouchard and S. M. Neveu and P. Renaud},
editor = {Zaremba M. Sasiadek J. Dolgui A.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84953850845&doi=10.1016%2fj.ifacol.2015.06.056&partnerID=40&md5=5eaa3cab6df7946f02c74e4aded68eac},
doi = {10.1016/j.ifacol.2015.06.056},
issn = {24058963},
year = {2015},
date = {2015-01-01},
booktitle = {IFAC-PapersOnLine},
volume = {28},
number = {3},
pages = {46–51},
abstract = {In this paper, we present the pipeline of data acquisition and analysis used in the ARViPL lab at the Montreal Philippe-Pinel Institute for different studies related to forensic psychiatry in Virtual Reality (VR) environment and we discuss the different challenges that we encounter during the experiments when combining different new technologies that help researchers to better understand the underlying mechanisms of various mental health disorders. © 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.},
note = {ISSN: 24058963
Issue: 3},
keywords = {Acquisition, Analysis, brain computer interface, Data acquisition, Electroencephalography, eye tracking, Eye-tracking, Forensic, Forensic engineering, Heat maps, Interfaces (computer), Psychiatry, Real time, virtual reality},
pubstate = {published},
tppubtype = {inproceedings}
}
In this paper, we present the pipeline of data acquisition and analysis used in the ARViPL lab at the Montreal Philippe-Pinel Institute for different studies related to forensic psychiatry in Virtual Reality (VR) environment and we discuss the different challenges that we encounter during the experiments when combining different new technologies that help researchers to better understand the underlying mechanisms of various mental health disorders. © 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
6.
Boukhalfi, T.; Joyal, C.; Bouchard, S.; Neveu, S. M.; Renaud, P.
Tools and techniques for real-time data acquisition and analysis in brain computer interface studies using qEEG and eye tracking in virtual reality environment Proceedings Article
In: A., Zaremba M. Sasiadek J. Dolgui (Ed.): IFAC-PapersOnLine, pp. 46–51, 2015, ISSN: 24058963.
Abstract | Links | BibTeX | Tags: Acquisition, Analysis, brain computer interface, Data acquisition, Electroencephalography, eye tracking, Eye-tracking, Forensic, Forensic engineering, Heat maps, Interfaces (computer), Psychiatry, Real time, virtual reality
@inproceedings{boukhalfiToolsTechniquesRealtime2015,
title = {Tools and techniques for real-time data acquisition and analysis in brain computer interface studies using qEEG and eye tracking in virtual reality environment},
author = {T. Boukhalfi and C. Joyal and S. Bouchard and S. M. Neveu and P. Renaud},
editor = {Zaremba M. Sasiadek J. Dolgui A.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84953850845&doi=10.1016%2fj.ifacol.2015.06.056&partnerID=40&md5=5eaa3cab6df7946f02c74e4aded68eac},
doi = {10.1016/j.ifacol.2015.06.056},
issn = {24058963},
year = {2015},
date = {2015-01-01},
booktitle = {IFAC-PapersOnLine},
volume = {28},
number = {3},
pages = {46–51},
abstract = {In this paper, we present the pipeline of data acquisition and analysis used in the ARViPL lab at the Montreal Philippe-Pinel Institute for different studies related to forensic psychiatry in Virtual Reality (VR) environment and we discuss the different challenges that we encounter during the experiments when combining different new technologies that help researchers to better understand the underlying mechanisms of various mental health disorders. © 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.},
keywords = {Acquisition, Analysis, brain computer interface, Data acquisition, Electroencephalography, eye tracking, Eye-tracking, Forensic, Forensic engineering, Heat maps, Interfaces (computer), Psychiatry, Real time, virtual reality},
pubstate = {published},
tppubtype = {inproceedings}
}
In this paper, we present the pipeline of data acquisition and analysis used in the ARViPL lab at the Montreal Philippe-Pinel Institute for different studies related to forensic psychiatry in Virtual Reality (VR) environment and we discuss the different challenges that we encounter during the experiments when combining different new technologies that help researchers to better understand the underlying mechanisms of various mental health disorders. © 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.