Slide
Centre Interdisciplinaire
de Recherche et d’Innovation
en Cybersécurité et Société
de Recherche et d’Innovation
en Cybersécurité et Société
1.
Malasi, J. -J. M.; Moudoud, H.; Missaoui, R.
A Lightweight Multimodal LLM-Based Intrusion Detection System for Open RAN Proceedings Article
In: IEEE Wirel. Commun. Netw. Conf. Workshops, WCNCW, Institute of Electrical and Electronics Engineers Inc., 2026, ISBN: 979-833157731-5 (ISBN), (Journal Abbreviation: IEEE Wirel. Commun. Netw. Conf. Workshops, WCNCW).
Abstract | Links | BibTeX | Tags: Benchmarking, Computational linguistics, Computer crime, Cyber security, Cybersecurity, Embedded systems, Embeddings, Intelligent controllers, Internet protocols, Intrusion Detection, intrusion detection system, Intrusion Detection System (IDS), Intrusion Detection Systems, Language model, Large language model, Large Language Models (LLMs), Mobile telecommunication systems, Multi-modal, Multi-modal learning, Multimodal Learning, Network security, Open RAN, Pipelines, RAN intelligent controller, RAN intelligent controller (RIC), Semantics
@inproceedings{malasiLightweightMultimodalLLMBased2026,
title = {A Lightweight Multimodal LLM-Based Intrusion Detection System for Open RAN},
author = {J. -J. M. Malasi and H. Moudoud and R. Missaoui},
url = {https://www.scopus.com/pages/publications/105043415034?origin=resultslist},
doi = {10.1109/WCNCW67598.2026.11555393},
isbn = {979-833157731-5 (ISBN)},
year = {2026},
date = {2026-01-01},
booktitle = {IEEE Wirel. Commun. Netw. Conf. Workshops, WCNCW},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {Open Radio Access Network architectures introduce unprecedented openness and programmability through RAN Intelligent Controllers, expanding the attack surface beyond traditional volumetric threats. Most existing intrusion detection systems for fifth-generation mobile networks and ORAN rely primarily on numerical Key Performance Indicators (KPIs), often overlooking the security-relevant semantics embedded in logs and control messages. This paper proposes LLM4IDS, a semantic-aware and multimodal intrusion detection system that fuses lightweight Large Language Model (LLM) embeddings of textified events with traditional tabular KPIs in a compact Transformer-based classifier. Evaluated on the realworld OpenIreland O-RAN dataset and two classical IP network benchmarks (UNSW-NB15 and CICIDS2017), LLM4IDS consistently matches or surpasses strong tabular baselines while maintaining high efficiency. On OpenIreland, it reaches nearperfect detection (F1-score $textbackslashapprox 1.0$) and yields large gains for application-layer and volumetric attacks compared to KPI-only models. Across datasets, the classifier maintains an approximately 4 MB footprint and sub-millisecond CPU inference latency; the frozen sentence-LLM encoder can be shared across tasks, and its embeddings can be cached or precomputed when required by the deployment pipeline. These results indicate that integrating semantic context through multimodal fusion can significantly enhance intrusion detection in O-RAN while remaining competitive on standard IP-based IDS tasks. To the best of our knowledge, this work is among the first to study a complete multimodal LLM-based IDS pipeline for O-RAN data with cross-domain evaluation on both O-RAN and classical IP benchmarks. © 2026 IEEE.},
note = {Journal Abbreviation: IEEE Wirel. Commun. Netw. Conf. Workshops, WCNCW},
keywords = {Benchmarking, Computational linguistics, Computer crime, Cyber security, Cybersecurity, Embedded systems, Embeddings, Intelligent controllers, Internet protocols, Intrusion Detection, intrusion detection system, Intrusion Detection System (IDS), Intrusion Detection Systems, Language model, Large language model, Large Language Models (LLMs), Mobile telecommunication systems, Multi-modal, Multi-modal learning, Multimodal Learning, Network security, Open RAN, Pipelines, RAN intelligent controller, RAN intelligent controller (RIC), Semantics},
pubstate = {published},
tppubtype = {inproceedings}
}
Open Radio Access Network architectures introduce unprecedented openness and programmability through RAN Intelligent Controllers, expanding the attack surface beyond traditional volumetric threats. Most existing intrusion detection systems for fifth-generation mobile networks and ORAN rely primarily on numerical Key Performance Indicators (KPIs), often overlooking the security-relevant semantics embedded in logs and control messages. This paper proposes LLM4IDS, a semantic-aware and multimodal intrusion detection system that fuses lightweight Large Language Model (LLM) embeddings of textified events with traditional tabular KPIs in a compact Transformer-based classifier. Evaluated on the realworld OpenIreland O-RAN dataset and two classical IP network benchmarks (UNSW-NB15 and CICIDS2017), LLM4IDS consistently matches or surpasses strong tabular baselines while maintaining high efficiency. On OpenIreland, it reaches nearperfect detection (F1-score $textbackslashapprox 1.0$) and yields large gains for application-layer and volumetric attacks compared to KPI-only models. Across datasets, the classifier maintains an approximately 4 MB footprint and sub-millisecond CPU inference latency; the frozen sentence-LLM encoder can be shared across tasks, and its embeddings can be cached or precomputed when required by the deployment pipeline. These results indicate that integrating semantic context through multimodal fusion can significantly enhance intrusion detection in O-RAN while remaining competitive on standard IP-based IDS tasks. To the best of our knowledge, this work is among the first to study a complete multimodal LLM-based IDS pipeline for O-RAN data with cross-domain evaluation on both O-RAN and classical IP benchmarks. © 2026 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.
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.
5.
Chabot, E.; Jaworski, E.; Renaud, P.
Pervasive Teledildonics: How AI Aims to Impact Human sexuality Proceedings Article
In: Proc. - IEEE/WIC Int. Conf. Web Intell. Intell. Agent Technol., WI-IAT, pp. 898–903, Institute of Electrical and Electronics Engineers Inc., Bangkok, Thailand, 2024, ISBN: 979-833150494-6 (ISBN).
Abstract | Links | BibTeX | Tags: Ambient intelligence, Anthropomorphic robots, Artificial intelligence, Artificial life, Capability awareness, Computing capability, Context- awareness, Cyber security, Human machine interaction, human-machine interactions, Humans-robot interactions, Industrial robots, Intelligent computing, Intelligent robots, Intelligent systems, Monitoring change, pervasive computing, Robot learning, Sexual satisfaction, sexual technologies, Sexual technology, Social robots, Teledildonic, teledildonics
@inproceedings{chabot_pervasive_2024,
title = {Pervasive Teledildonics: How AI Aims to Impact Human sexuality},
author = {E. Chabot and E. Jaworski and P. Renaud},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105007140928&doi=10.1109%2FWI-IAT62293.2024.00146&partnerID=40&md5=0e1c4d50642661b589db24542641bdf0},
doi = {10.1109/WI-IAT62293.2024.00146},
isbn = {979-833150494-6 (ISBN)},
year = {2024},
date = {2024-01-01},
booktitle = {Proc. - IEEE/WIC Int. Conf. Web Intell. Intell. Agent Technol., WI-IAT},
pages = {898–903},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
address = {Bangkok, Thailand},
abstract = {Since the Covid-19 pandemic, sexual technology sales have increased all over the world, especially for devices allowing users to connect with each other or the internet. The convergence of sexualtechnology with pervasivecomputing and artificial intelligence (AI) introduces a new era of human-robot interactions. Sexual technology, ranging from smart sex toys to humanoid sex robots, now incorporates pervasive computing principles and/or AI to enhance intimate experiences. These devices leverage ubiquitous computing capabilities, adaptability, and context awareness to increase sexual satisfaction and integrate into users' lives. The integration of these technologies into intimate interactions raises questions on how these changes will affect different Webs of Life, in eluding but not limited to, the Web of People, the Web of Things and the Web of Health. From health and cybersecurity risks to the reshaping of human-human and human-robot interactions, this paper addresses the challenges at the intersection of sexual technologies, pervasive computing, AI and human-machine interactions. Emphasizing the importance of monitoring changes and increasing cybersecurity to create safe, consensual, and secure intimate experiences. © 2024 IEEE.},
keywords = {Ambient intelligence, Anthropomorphic robots, Artificial intelligence, Artificial life, Capability awareness, Computing capability, Context- awareness, Cyber security, Human machine interaction, human-machine interactions, Humans-robot interactions, Industrial robots, Intelligent computing, Intelligent robots, Intelligent systems, Monitoring change, pervasive computing, Robot learning, Sexual satisfaction, sexual technologies, Sexual technology, Social robots, Teledildonic, teledildonics},
pubstate = {published},
tppubtype = {inproceedings}
}
Since the Covid-19 pandemic, sexual technology sales have increased all over the world, especially for devices allowing users to connect with each other or the internet. The convergence of sexualtechnology with pervasivecomputing and artificial intelligence (AI) introduces a new era of human-robot interactions. Sexual technology, ranging from smart sex toys to humanoid sex robots, now incorporates pervasive computing principles and/or AI to enhance intimate experiences. These devices leverage ubiquitous computing capabilities, adaptability, and context awareness to increase sexual satisfaction and integrate into users' lives. The integration of these technologies into intimate interactions raises questions on how these changes will affect different Webs of Life, in eluding but not limited to, the Web of People, the Web of Things and the Web of Health. From health and cybersecurity risks to the reshaping of human-human and human-robot interactions, this paper addresses the challenges at the intersection of sexual technologies, pervasive computing, AI and human-machine interactions. Emphasizing the importance of monitoring changes and increasing cybersecurity to create safe, consensual, and secure intimate experiences. © 2024 IEEE.
6.
Chabot, E.; Jaworski, E.; Renaud, P.
Pervasive Teledildonics: How AI Aims to Impact Human sexuality Proceedings Article
In: Proc. - IEEE/WIC Int. Conf. Web Intell. Intell. Agent Technol., WI-IAT, pp. 898–903, Institute of Electrical and Electronics Engineers Inc., 2024, ISBN: 979-833150494-6 (ISBN).
Abstract | Links | BibTeX | Tags: Ambient intelligence, Anthropomorphic robots, Artificial intelligence, Artificial life, Capability awareness, Computing capability, Context- awareness, Cyber security, Human machine interaction, human-machine interactions, Humans-robot interactions, Industrial robots, Intelligent computing, Intelligent robots, Intelligent systems, Monitoring change, pervasive computing, Robot learning, Sexual satisfaction, sexual technologies, Sexual technology, Social robots, Teledildonic, teledildonics
@inproceedings{chabotPervasiveTeledildonicsHow2024,
title = {Pervasive Teledildonics: How AI Aims to Impact Human sexuality},
author = {E. Chabot and E. Jaworski and P. Renaud},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105007140928&doi=10.1109%2FWI-IAT62293.2024.00146&partnerID=40&md5=0e1c4d50642661b589db24542641bdf0},
doi = {10.1109/WI-IAT62293.2024.00146},
isbn = {979-833150494-6 (ISBN)},
year = {2024},
date = {2024-01-01},
booktitle = {Proc. - IEEE/WIC Int. Conf. Web Intell. Intell. Agent Technol., WI-IAT},
pages = {898–903},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {Since the Covid-19 pandemic, sexual technology sales have increased all over the world, especially for devices allowing users to connect with each other or the internet. The convergence of sexualtechnology with pervasivecomputing and artificial intelligence (AI) introduces a new era of human-robot interactions. Sexual technology, ranging from smart sex toys to humanoid sex robots, now incorporates pervasive computing principles and/or AI to enhance intimate experiences. These devices leverage ubiquitous computing capabilities, adaptability, and context awareness to increase sexual satisfaction and integrate into users' lives. The integration of these technologies into intimate interactions raises questions on how these changes will affect different Webs of Life, in eluding but not limited to, the Web of People, the Web of Things and the Web of Health. From health and cybersecurity risks to the reshaping of human-human and human-robot interactions, this paper addresses the challenges at the intersection of sexual technologies, pervasive computing, AI and human-machine interactions. Emphasizing the importance of monitoring changes and increasing cybersecurity to create safe, consensual, and secure intimate experiences. © 2024 IEEE.},
keywords = {Ambient intelligence, Anthropomorphic robots, Artificial intelligence, Artificial life, Capability awareness, Computing capability, Context- awareness, Cyber security, Human machine interaction, human-machine interactions, Humans-robot interactions, Industrial robots, Intelligent computing, Intelligent robots, Intelligent systems, Monitoring change, pervasive computing, Robot learning, Sexual satisfaction, sexual technologies, Sexual technology, Social robots, Teledildonic, teledildonics},
pubstate = {published},
tppubtype = {inproceedings}
}
Since the Covid-19 pandemic, sexual technology sales have increased all over the world, especially for devices allowing users to connect with each other or the internet. The convergence of sexualtechnology with pervasivecomputing and artificial intelligence (AI) introduces a new era of human-robot interactions. Sexual technology, ranging from smart sex toys to humanoid sex robots, now incorporates pervasive computing principles and/or AI to enhance intimate experiences. These devices leverage ubiquitous computing capabilities, adaptability, and context awareness to increase sexual satisfaction and integrate into users' lives. The integration of these technologies into intimate interactions raises questions on how these changes will affect different Webs of Life, in eluding but not limited to, the Web of People, the Web of Things and the Web of Health. From health and cybersecurity risks to the reshaping of human-human and human-robot interactions, this paper addresses the challenges at the intersection of sexual technologies, pervasive computing, AI and human-machine interactions. Emphasizing the importance of monitoring changes and increasing cybersecurity to create safe, consensual, and secure intimate experiences. © 2024 IEEE.