Slide
Centre Interdisciplinaire
de Recherche et d’Innovation
en Cybersécurité et Société
de Recherche et d’Innovation
en Cybersécurité et Société
1.
Hamadene, A.; Allili, M. S.
Cross-Model Deepfake Detection Through Contourlet-Based Inter-Channel Spectral Analysis Journal Article
In: IEEE Transactions on Biometrics, Behavior, and Identity Science, 2026, ISSN: 26376407 (ISSN).
Abstract | Links | BibTeX | Tags: Attribution, Computer forensics, Computer vision, Contourlet transform, Contourlets, Cross model, Cross-Model Generalization, Deep learning, Deepfake detection, Forensic engineering, Image Enhancement, Inter-channel contourlet feature, Inter-Channel Contourlet Features, Model generalization, Performance, Public trust, Spectral analyze, Spectrum analysis
@article{hamadeneCrossModelDeepfakeDetection2026,
title = {Cross-Model Deepfake Detection Through Contourlet-Based Inter-Channel Spectral Analysis},
author = {A. Hamadene and M. S. Allili},
url = {https://www.scopus.com/pages/publications/105038690534?origin=resultslist},
doi = {10.1109/TBIOM.2026.3687469},
issn = {26376407 (ISSN)},
year = {2026},
date = {2026-01-01},
journal = {IEEE Transactions on Biometrics, Behavior, and Identity Science},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {The rapid advancement of generative AI has fueled the proliferation of highly realistic deepfakes, raising growing concerns for public trust, digital forensics, and societal stability. While deep learning-based detectors have shown promising results in controlled settings, their effectiveness diminishes significantly across different datasets or unseen deepfakes. This performance drop reveals a core limitation: overfitting to dataset-specific artifacts and a failure to learn robust, content-agnostic forensic cues. In this work, we study a novel deepfake characterization that targets inter-channel spectral inconsistencies, a subtle but critical artifact of AI-generated imagery. Departing from conventional approaches that focus on spatial irregularities or within-channel frequency analysis, our method leverages the Contourlet Transform (CT) to extract high-frequency, multiscale, and multidirectional features across color channels. These features reveal latent spectral distortions and structural misalignments that persist across different generative models, including both GANs and Diffusion Models. Extensive experiments show that our approach generalizes well across datasets, achieving strong performance in both model-specific and cross-model detection tasks. Our findings highlight the promise of inter-channel spectral analysis for advancing the robustness and generalizability of deepfake detection systems. © 2019 IEEE.},
keywords = {Attribution, Computer forensics, Computer vision, Contourlet transform, Contourlets, Cross model, Cross-Model Generalization, Deep learning, Deepfake detection, Forensic engineering, Image Enhancement, Inter-channel contourlet feature, Inter-Channel Contourlet Features, Model generalization, Performance, Public trust, Spectral analyze, Spectrum analysis},
pubstate = {published},
tppubtype = {article}
}
The rapid advancement of generative AI has fueled the proliferation of highly realistic deepfakes, raising growing concerns for public trust, digital forensics, and societal stability. While deep learning-based detectors have shown promising results in controlled settings, their effectiveness diminishes significantly across different datasets or unseen deepfakes. This performance drop reveals a core limitation: overfitting to dataset-specific artifacts and a failure to learn robust, content-agnostic forensic cues. In this work, we study a novel deepfake characterization that targets inter-channel spectral inconsistencies, a subtle but critical artifact of AI-generated imagery. Departing from conventional approaches that focus on spatial irregularities or within-channel frequency analysis, our method leverages the Contourlet Transform (CT) to extract high-frequency, multiscale, and multidirectional features across color channels. These features reveal latent spectral distortions and structural misalignments that persist across different generative models, including both GANs and Diffusion Models. Extensive experiments show that our approach generalizes well across datasets, achieving strong performance in both model-specific and cross-model detection tasks. Our findings highlight the promise of inter-channel spectral analysis for advancing the robustness and generalizability of deepfake detection systems. © 2019 IEEE.
2.
Brideau-Duquette, M.; Côté, S. S. -P.; Boukhalfi, T.; Renaud, P.
Forensic Psychiatry and Big Data: Towards a Cyberphysical System in Service of Clinic, Research and Cybersecurity Proceedings Article
In: B., Boulay; T., Di Mascio; E., Tovar; C., Meinel (Ed.): International Conference on Computer Supported Education, CSEDU - Proceedings, pp. 856–864, Science and Technology Publications, Lda, 2025, ISBN: 21845026 (ISSN); 978-989758746-7 (ISBN), (Journal Abbreviation: International Conference on Computer Supported Education, CSEDU - Proceedings).
Abstract | Links | BibTeX | Tags: Artificial intelligence, Artificial life, Behavioral research, Computer forensics, Cyber security, Cyber-physical systems, Cyberphysical System, Cybersecurity, Data Lake, Data repositories, Extended Reality, Forensic engineering, Forensic psychiatry, Intelligent computing, prediction, Prevention, Research efforts, Social Engineering, Sociology, System in services
@inproceedings{brideau-duquette_forensic_2025,
title = {Forensic Psychiatry and Big Data: Towards a Cyberphysical System in Service of Clinic, Research and Cybersecurity},
author = {M. Brideau-Duquette and S. S. -P. Côté and T. Boukhalfi and P. Renaud},
editor = {Boulay B. and Di Mascio T. and Tovar E. and Meinel C.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105003621528&doi=10.5220%2f0013496100003932&partnerID=40&md5=ee442c9113f1104973b40ef698bc5d7d},
doi = {10.5220/0013496100003932},
isbn = {21845026 (ISSN); 978-989758746-7 (ISBN)},
year = {2025},
date = {2025-01-01},
booktitle = {International Conference on Computer Supported Education, CSEDU - Proceedings},
volume = {1},
pages = {856–864},
publisher = {Science and Technology Publications, Lda},
abstract = {The advent of big data and artificial intelligence has led to the elaboration of computational psychiatry. In parallel, great progress has been made with extended reality (XR) technologies. In this article, we propose to build a forensic cyberphysical system (CPS) that, with a data lake as its computational and data repository core, will support clinical and research efforts in forensic psychiatry, this in both intramural and extramural settings. The proposed CPS requires offender's data (notably clinical, behavioural and physiological), but also emphasises the collection of such data in various XR contexts. The same data would be used to train machine and deep learning, artificial intelligence, algorithms. Beyond the direct feedback these algorithms could give to forensic specialists, they could help build forensic digital twins. They could also serve in the fine tuning of XR usage with offenders. This paper concludes with human-centered cybersecurity concerns and opportunities the same CPS would imply. The proximity between a forensic and XR-supported CPS and social engineering will be addressed, and special consideration will be given to the opportunity for situational awareness training with offenders. We conclude by sketching ethical and implementation challenges that would require future inquiring. Copyright © 2025 by SCITEPRESS - Science and Technology Publications, Lda.},
note = {Journal Abbreviation: International Conference on Computer Supported Education, CSEDU - Proceedings},
keywords = {Artificial intelligence, Artificial life, Behavioral research, Computer forensics, Cyber security, Cyber-physical systems, Cyberphysical System, Cybersecurity, Data Lake, Data repositories, Extended Reality, Forensic engineering, Forensic psychiatry, Intelligent computing, prediction, Prevention, Research efforts, Social Engineering, Sociology, System in services},
pubstate = {published},
tppubtype = {inproceedings}
}
The advent of big data and artificial intelligence has led to the elaboration of computational psychiatry. In parallel, great progress has been made with extended reality (XR) technologies. In this article, we propose to build a forensic cyberphysical system (CPS) that, with a data lake as its computational and data repository core, will support clinical and research efforts in forensic psychiatry, this in both intramural and extramural settings. The proposed CPS requires offender's data (notably clinical, behavioural and physiological), but also emphasises the collection of such data in various XR contexts. The same data would be used to train machine and deep learning, artificial intelligence, algorithms. Beyond the direct feedback these algorithms could give to forensic specialists, they could help build forensic digital twins. They could also serve in the fine tuning of XR usage with offenders. This paper concludes with human-centered cybersecurity concerns and opportunities the same CPS would imply. The proximity between a forensic and XR-supported CPS and social engineering will be addressed, and special consideration will be given to the opportunity for situational awareness training with offenders. We conclude by sketching ethical and implementation challenges that would require future inquiring. Copyright © 2025 by SCITEPRESS - Science and Technology Publications, Lda.
3.
Brideau-Duquette, M.; Côté, S. S. -P.; Boukhalfi, T.; Renaud, P.
Forensic Psychiatry and Big Data: Towards a Cyberphysical System in Service of Clinic, Research and Cybersecurity Proceedings Article
In: B., Boulay; T., Di Mascio; E., Tovar; C., Meinel (Ed.): International Conference on Computer Supported Education, CSEDU - Proceedings, pp. 856–864, Science and Technology Publications, Lda, 2025, ISBN: 21845026 (ISSN); 978-989758746-7 (ISBN), (Journal Abbreviation: International Conference on Computer Supported Education, CSEDU - Proceedings).
Abstract | Links | BibTeX | Tags: Artificial intelligence, Artificial life, Behavioral research, Computer forensics, Cyber security, Cyber-physical systems, Cyberphysical System, Cybersecurity, Data Lake, Data repositories, Extended Reality, Forensic engineering, Forensic psychiatry, Intelligent computing, prediction, Prevention, Research efforts, Social Engineering, Sociology, System in services
@inproceedings{brideau-duquetteForensicPsychiatryBig2025a,
title = {Forensic Psychiatry and Big Data: Towards a Cyberphysical System in Service of Clinic, Research and Cybersecurity},
author = {M. Brideau-Duquette and S. S. -P. Côté and T. Boukhalfi and P. Renaud},
editor = {Boulay B. and Di Mascio T. and Tovar E. and Meinel C.},
url = {https://www.scopus.com/pages/publications/105003621528?origin=resultslist},
doi = {10.5220/0013496100003932},
isbn = {21845026 (ISSN); 978-989758746-7 (ISBN)},
year = {2025},
date = {2025-01-01},
booktitle = {International Conference on Computer Supported Education, CSEDU - Proceedings},
volume = {1},
pages = {856–864},
publisher = {Science and Technology Publications, Lda},
abstract = {The advent of big data and artificial intelligence has led to the elaboration of computational psychiatry. In parallel, great progress has been made with extended reality (XR) technologies. In this article, we propose to build a forensic cyberphysical system (CPS) that, with a data lake as its computational and data repository core, will support clinical and research efforts in forensic psychiatry, this in both intramural and extramural settings. The proposed CPS requires offender's data (notably clinical, behavioural and physiological), but also emphasises the collection of such data in various XR contexts. The same data would be used to train machine and deep learning, artificial intelligence, algorithms. Beyond the direct feedback these algorithms could give to forensic specialists, they could help build forensic digital twins. They could also serve in the fine tuning of XR usage with offenders. This paper concludes with human-centered cybersecurity concerns and opportunities the same CPS would imply. The proximity between a forensic and XR-supported CPS and social engineering will be addressed, and special consideration will be given to the opportunity for situational awareness training with offenders. We conclude by sketching ethical and implementation challenges that would require future inquiring. Copyright © 2025 by SCITEPRESS - Science and Technology Publications, Lda.},
note = {Journal Abbreviation: International Conference on Computer Supported Education, CSEDU - Proceedings},
keywords = {Artificial intelligence, Artificial life, Behavioral research, Computer forensics, Cyber security, Cyber-physical systems, Cyberphysical System, Cybersecurity, Data Lake, Data repositories, Extended Reality, Forensic engineering, Forensic psychiatry, Intelligent computing, prediction, Prevention, Research efforts, Social Engineering, Sociology, System in services},
pubstate = {published},
tppubtype = {inproceedings}
}
The advent of big data and artificial intelligence has led to the elaboration of computational psychiatry. In parallel, great progress has been made with extended reality (XR) technologies. In this article, we propose to build a forensic cyberphysical system (CPS) that, with a data lake as its computational and data repository core, will support clinical and research efforts in forensic psychiatry, this in both intramural and extramural settings. The proposed CPS requires offender's data (notably clinical, behavioural and physiological), but also emphasises the collection of such data in various XR contexts. The same data would be used to train machine and deep learning, artificial intelligence, algorithms. Beyond the direct feedback these algorithms could give to forensic specialists, they could help build forensic digital twins. They could also serve in the fine tuning of XR usage with offenders. This paper concludes with human-centered cybersecurity concerns and opportunities the same CPS would imply. The proximity between a forensic and XR-supported CPS and social engineering will be addressed, and special consideration will be given to the opportunity for situational awareness training with offenders. We conclude by sketching ethical and implementation challenges that would require future inquiring. Copyright © 2025 by SCITEPRESS - Science and Technology Publications, Lda.
4.
Saini, H. K.; Rani, S.; Ouaissa, M.; Ouaissa, M.; Houda, Z. A. El; Moudoud, H.
CRC Press, 2025, ISBN: 978-100364032-5 (ISBN); 978-104107046-7 (ISBN), (Journal Abbreviation: Digit. Forensics in Next-Gener. Internet of Med. Things: Balanc. Secur. and Sustain. Pages: 283 Publication Title: Digit. Forensics in Next-Gener. Internet of Med. Things: Balanc. Secur. and Sustain.).
Abstract | Links | BibTeX | Tags: Case-studies, Computer forensics, Forensic Techniques, Internet of things, Machine data, Medical computing, Medical data, Medical practitioner, Network security, Next generation Internet, Patient data, Real-world, Security challenges, Security solutions, sustainable development
@book{sainiDigitalForensicsNextGeneration2025,
title = {Digital Forensics in Next-Generation Internet of Medical Things: Balancing Security and Sustainability},
author = {H. K. Saini and S. Rani and M. Ouaissa and M. Ouaissa and Z. A. El Houda and H. Moudoud},
url = {https://www.scopus.com/pages/publications/105024400792?origin=resultslist},
doi = {10.1201/9781003640325},
isbn = {978-100364032-5 (ISBN); 978-104107046-7 (ISBN)},
year = {2025},
date = {2025-01-01},
publisher = {CRC Press},
series = {Digital Forensics in Next-Generation Internet of Medical Things: Balancing Security and Sustainability},
abstract = {This book provides a comprehensive exploration of the security challenges and solutions with digital sustainability in the rapidly evolving digital landscape of digital forensics. It explores the details of protecting Internet of Medical Things (IoMT) environments, where the medical data, patient data, and machine data are at high risk with the digital experiences. The book seeks to provide researchers, medical practitioners, and IT specialists with important information. It aims to set the stage for a future in which security and efficiency in IoMT smoothly blend through real-world case studies. Key themes cover IoMT-specific forensic techniques, the difficulties of striking a balance between environmental responsibility and security, and creative solutions that combine the two viewpoints. © 2026 selection and editorial matter, Hemant Kumar Saini, Sita Rani, Mariya Ouaissa, Mariyam Ouaissa, Zakaria Abou El Houda, and Hajar Moudoud. All rights reserved.},
note = {Journal Abbreviation: Digit. Forensics in Next-Gener. Internet of Med. Things: Balanc. Secur. and Sustain.
Pages: 283
Publication Title: Digit. Forensics in Next-Gener. Internet of Med. Things: Balanc. Secur. and Sustain.},
keywords = {Case-studies, Computer forensics, Forensic Techniques, Internet of things, Machine data, Medical computing, Medical data, Medical practitioner, Network security, Next generation Internet, Patient data, Real-world, Security challenges, Security solutions, sustainable development},
pubstate = {published},
tppubtype = {book}
}
This book provides a comprehensive exploration of the security challenges and solutions with digital sustainability in the rapidly evolving digital landscape of digital forensics. It explores the details of protecting Internet of Medical Things (IoMT) environments, where the medical data, patient data, and machine data are at high risk with the digital experiences. The book seeks to provide researchers, medical practitioners, and IT specialists with important information. It aims to set the stage for a future in which security and efficiency in IoMT smoothly blend through real-world case studies. Key themes cover IoMT-specific forensic techniques, the difficulties of striking a balance between environmental responsibility and security, and creative solutions that combine the two viewpoints. © 2026 selection and editorial matter, Hemant Kumar Saini, Sita Rani, Mariya Ouaissa, Mariyam Ouaissa, Zakaria Abou El Houda, and Hajar Moudoud. All rights reserved.
5.
Brideau-Duquette, M.; Côté, S. S. -P.; Boukhalfi, T.; Renaud, P.
Forensic Psychiatry and Big Data: Towards a Cyberphysical System in Service of Clinic, Research and Cybersecurity Proceedings Article
In: B., Boulay; T., Di Mascio; E., Tovar; C., Meinel (Ed.): International Conference on Computer Supported Education, CSEDU - Proceedings, pp. 856–864, Science and Technology Publications, Lda, 2025, ISBN: 21845026 (ISSN); 978-989758746-7 (ISBN), (Journal Abbreviation: International Conference on Computer Supported Education, CSEDU - Proceedings).
Abstract | Links | BibTeX | Tags: Artificial intelligence, Artificial life, Behavioral research, Computer forensics, Cyber security, Cyber-physical systems, Cyberphysical System, Cybersecurity, Data Lake, Data repositories, Extended Reality, Forensic engineering, Forensic psychiatry, Intelligent computing, prediction, Prevention, Research efforts, Social Engineering, Sociology, System in services
@inproceedings{brideau-duquetteForensicPsychiatryBig2025,
title = {Forensic Psychiatry and Big Data: Towards a Cyberphysical System in Service of Clinic, Research and Cybersecurity},
author = {M. Brideau-Duquette and S. S. -P. Côté and T. Boukhalfi and P. Renaud},
editor = {Boulay B. and Di Mascio T. and Tovar E. and Meinel C.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105003621528&doi=10.5220%2f0013496100003932&partnerID=40&md5=ee442c9113f1104973b40ef698bc5d7d},
doi = {10.5220/0013496100003932},
isbn = {21845026 (ISSN); 978-989758746-7 (ISBN)},
year = {2025},
date = {2025-01-01},
booktitle = {International Conference on Computer Supported Education, CSEDU - Proceedings},
volume = {1},
pages = {856–864},
publisher = {Science and Technology Publications, Lda},
abstract = {The advent of big data and artificial intelligence has led to the elaboration of computational psychiatry. In parallel, great progress has been made with extended reality (XR) technologies. In this article, we propose to build a forensic cyberphysical system (CPS) that, with a data lake as its computational and data repository core, will support clinical and research efforts in forensic psychiatry, this in both intramural and extramural settings. The proposed CPS requires offender's data (notably clinical, behavioural and physiological), but also emphasises the collection of such data in various XR contexts. The same data would be used to train machine and deep learning, artificial intelligence, algorithms. Beyond the direct feedback these algorithms could give to forensic specialists, they could help build forensic digital twins. They could also serve in the fine tuning of XR usage with offenders. This paper concludes with human-centered cybersecurity concerns and opportunities the same CPS would imply. The proximity between a forensic and XR-supported CPS and social engineering will be addressed, and special consideration will be given to the opportunity for situational awareness training with offenders. We conclude by sketching ethical and implementation challenges that would require future inquiring. Copyright © 2025 by SCITEPRESS - Science and Technology Publications, Lda.},
note = {Journal Abbreviation: International Conference on Computer Supported Education, CSEDU - Proceedings},
keywords = {Artificial intelligence, Artificial life, Behavioral research, Computer forensics, Cyber security, Cyber-physical systems, Cyberphysical System, Cybersecurity, Data Lake, Data repositories, Extended Reality, Forensic engineering, Forensic psychiatry, Intelligent computing, prediction, Prevention, Research efforts, Social Engineering, Sociology, System in services},
pubstate = {published},
tppubtype = {inproceedings}
}
The advent of big data and artificial intelligence has led to the elaboration of computational psychiatry. In parallel, great progress has been made with extended reality (XR) technologies. In this article, we propose to build a forensic cyberphysical system (CPS) that, with a data lake as its computational and data repository core, will support clinical and research efforts in forensic psychiatry, this in both intramural and extramural settings. The proposed CPS requires offender's data (notably clinical, behavioural and physiological), but also emphasises the collection of such data in various XR contexts. The same data would be used to train machine and deep learning, artificial intelligence, algorithms. Beyond the direct feedback these algorithms could give to forensic specialists, they could help build forensic digital twins. They could also serve in the fine tuning of XR usage with offenders. This paper concludes with human-centered cybersecurity concerns and opportunities the same CPS would imply. The proximity between a forensic and XR-supported CPS and social engineering will be addressed, and special consideration will be given to the opportunity for situational awareness training with offenders. We conclude by sketching ethical and implementation challenges that would require future inquiring. Copyright © 2025 by SCITEPRESS - Science and Technology Publications, Lda.
6.
Renaud, P.; Trottier, D.; Rouleau, J. -L.; Goyette, M.; Saumur, C.; Boukhalfi, T.; Bouchard, S.
Using immersive virtual reality and anatomically correct computer-generated characters in the forensic assessment of deviant sexual preferences Journal Article
In: Virtual Reality, vol. 18, no. 1, pp. 37–47, 2014, ISSN: 13594338, (Publisher: Springer London).
Abstract | Links | BibTeX | Tags: Area Under the Curve (AUC), Classification accuracy, Computer forensics, Computer generated characters, Deregulation, Gears, Immersive virtual reality, Pedophilia, Plethysmography, Receiver operating characteristic analysis, Self regulation, Virtual addresses, Virtual character, virtual reality
@article{renaud_using_2014,
title = {Using immersive virtual reality and anatomically correct computer-generated characters in the forensic assessment of deviant sexual preferences},
author = {P. Renaud and D. Trottier and J. -L. Rouleau and M. Goyette and C. Saumur and T. Boukhalfi and S. Bouchard},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84893969900&doi=10.1007%2fs10055-013-0235-8&partnerID=40&md5=847ee510fd6f3c30ec6285071e0df167},
doi = {10.1007/s10055-013-0235-8},
issn = {13594338},
year = {2014},
date = {2014-01-01},
journal = {Virtual Reality},
volume = {18},
number = {1},
pages = {37–47},
publisher = {Springer London},
abstract = {Penile plethysmography (PPG) is the gold standard for the assessment of sexual interests, especially among sex offenders of children. Nonetheless, this method faces some ethical limitations inherent to the nature of its stimuli and could benefit from the improvement of its ecological validity. The use of computer-generated characters (CGC) in virtual immersion for PPG assessment might help address these issues. A new application developed to design made-to-measure anatomically correct virtual characters compatible with the Tanner developmental stages is presented. The main purpose of this study was to determine how the virtual reality (VR) modality compares to the standard auditory modality on their capacity to generate sexual arousal profiles and deviance differentials indicative of sexual interests. The erectile responses of 22 sex offenders of children and 42 non-deviant adult males were recorded. While both stimulus modalities generated significantly different genital arousal profiles for sex offenders of children and non-deviant males, deviance differentials calculated from the VR modality allowed for significantly higher classification accuracy. Performing receiver operating characteristic analyses further assessed discriminant potential. Auditory modality yielded an area under the curve (AUC) of 0.79 (SE = 0.059) while CGC in VR yielded an AUC of 0.90 (SE = 0.052). Overall, results suggest that the VR modality allows significantly better group classification accuracy and discriminant validity than audio stimuli, which provide empirical support for the use of this new method for PPG assessment. Additionally, the potential use of VR in interventions pertaining to self-regulation of sexual offending is addressed in conclusion. © 2013 Springer-Verlag London.},
note = {Publisher: Springer London},
keywords = {Area Under the Curve (AUC), Classification accuracy, Computer forensics, Computer generated characters, Deregulation, Gears, Immersive virtual reality, Pedophilia, Plethysmography, Receiver operating characteristic analysis, Self regulation, Virtual addresses, Virtual character, virtual reality},
pubstate = {published},
tppubtype = {article}
}
Penile plethysmography (PPG) is the gold standard for the assessment of sexual interests, especially among sex offenders of children. Nonetheless, this method faces some ethical limitations inherent to the nature of its stimuli and could benefit from the improvement of its ecological validity. The use of computer-generated characters (CGC) in virtual immersion for PPG assessment might help address these issues. A new application developed to design made-to-measure anatomically correct virtual characters compatible with the Tanner developmental stages is presented. The main purpose of this study was to determine how the virtual reality (VR) modality compares to the standard auditory modality on their capacity to generate sexual arousal profiles and deviance differentials indicative of sexual interests. The erectile responses of 22 sex offenders of children and 42 non-deviant adult males were recorded. While both stimulus modalities generated significantly different genital arousal profiles for sex offenders of children and non-deviant males, deviance differentials calculated from the VR modality allowed for significantly higher classification accuracy. Performing receiver operating characteristic analyses further assessed discriminant potential. Auditory modality yielded an area under the curve (AUC) of 0.79 (SE = 0.059) while CGC in VR yielded an AUC of 0.90 (SE = 0.052). Overall, results suggest that the VR modality allows significantly better group classification accuracy and discriminant validity than audio stimuli, which provide empirical support for the use of this new method for PPG assessment. Additionally, the potential use of VR in interventions pertaining to self-regulation of sexual offending is addressed in conclusion. © 2013 Springer-Verlag London.
7.
Renaud, P.; Trottier, D.; Rouleau, J. -L.; Goyette, M.; Saumur, C.; Boukhalfi, T.; Bouchard, S.
Using immersive virtual reality and anatomically correct computer-generated characters in the forensic assessment of deviant sexual preferences Journal Article
In: Virtual Reality, vol. 18, no. 1, pp. 37–47, 2014, ISSN: 13594338.
Abstract | Links | BibTeX | Tags: Area Under the Curve (AUC), Classification accuracy, Computer forensics, Computer generated characters, Deregulation, Gears, Immersive virtual reality, Pedophilia, Plethysmography, Receiver operating characteristic analysis, Self regulation, Virtual addresses, Virtual character, virtual reality
@article{renaudUsingImmersiveVirtual2014,
title = {Using immersive virtual reality and anatomically correct computer-generated characters in the forensic assessment of deviant sexual preferences},
author = {P. Renaud and D. Trottier and J. -L. Rouleau and M. Goyette and C. Saumur and T. Boukhalfi and S. Bouchard},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84893969900&doi=10.1007%2fs10055-013-0235-8&partnerID=40&md5=847ee510fd6f3c30ec6285071e0df167},
doi = {10.1007/s10055-013-0235-8},
issn = {13594338},
year = {2014},
date = {2014-01-01},
journal = {Virtual Reality},
volume = {18},
number = {1},
pages = {37–47},
publisher = {Springer London},
abstract = {Penile plethysmography (PPG) is the gold standard for the assessment of sexual interests, especially among sex offenders of children. Nonetheless, this method faces some ethical limitations inherent to the nature of its stimuli and could benefit from the improvement of its ecological validity. The use of computer-generated characters (CGC) in virtual immersion for PPG assessment might help address these issues. A new application developed to design made-to-measure anatomically correct virtual characters compatible with the Tanner developmental stages is presented. The main purpose of this study was to determine how the virtual reality (VR) modality compares to the standard auditory modality on their capacity to generate sexual arousal profiles and deviance differentials indicative of sexual interests. The erectile responses of 22 sex offenders of children and 42 non-deviant adult males were recorded. While both stimulus modalities generated significantly different genital arousal profiles for sex offenders of children and non-deviant males, deviance differentials calculated from the VR modality allowed for significantly higher classification accuracy. Performing receiver operating characteristic analyses further assessed discriminant potential. Auditory modality yielded an area under the curve (AUC) of 0.79 (SE = 0.059) while CGC in VR yielded an AUC of 0.90 (SE = 0.052). Overall, results suggest that the VR modality allows significantly better group classification accuracy and discriminant validity than audio stimuli, which provide empirical support for the use of this new method for PPG assessment. Additionally, the potential use of VR in interventions pertaining to self-regulation of sexual offending is addressed in conclusion. © 2013 Springer-Verlag London.},
keywords = {Area Under the Curve (AUC), Classification accuracy, Computer forensics, Computer generated characters, Deregulation, Gears, Immersive virtual reality, Pedophilia, Plethysmography, Receiver operating characteristic analysis, Self regulation, Virtual addresses, Virtual character, virtual reality},
pubstate = {published},
tppubtype = {article}
}
Penile plethysmography (PPG) is the gold standard for the assessment of sexual interests, especially among sex offenders of children. Nonetheless, this method faces some ethical limitations inherent to the nature of its stimuli and could benefit from the improvement of its ecological validity. The use of computer-generated characters (CGC) in virtual immersion for PPG assessment might help address these issues. A new application developed to design made-to-measure anatomically correct virtual characters compatible with the Tanner developmental stages is presented. The main purpose of this study was to determine how the virtual reality (VR) modality compares to the standard auditory modality on their capacity to generate sexual arousal profiles and deviance differentials indicative of sexual interests. The erectile responses of 22 sex offenders of children and 42 non-deviant adult males were recorded. While both stimulus modalities generated significantly different genital arousal profiles for sex offenders of children and non-deviant males, deviance differentials calculated from the VR modality allowed for significantly higher classification accuracy. Performing receiver operating characteristic analyses further assessed discriminant potential. Auditory modality yielded an area under the curve (AUC) of 0.79 (SE = 0.059) while CGC in VR yielded an AUC of 0.90 (SE = 0.052). Overall, results suggest that the VR modality allows significantly better group classification accuracy and discriminant validity than audio stimuli, which provide empirical support for the use of this new method for PPG assessment. Additionally, the potential use of VR in interventions pertaining to self-regulation of sexual offending is addressed in conclusion. © 2013 Springer-Verlag London.