Slide
Centre Interdisciplinaire
de Recherche et d’Innovation
en Cybersécurité et Société
de Recherche et d’Innovation
en Cybersécurité et Société
1.
António, H.; Albuquerque, S.; de Castro, M. Vieira; Bouchard, S.; Gamito, P.; Pinto, R. J.
In: Psychiatry International, vol. 7, no. 4, 2026, ISSN: 26735318 (ISSN).
Abstract | Links | BibTeX | Tags: adult, Anxiety, article, cross-sectional study, decision making, Depression, DSM-5, female, Global Severity Index, hostility, human, human experiment, Latent Class Analysis, LEC-5, major clinical study, male, paranoia, phobia, police, Positive symptom distress index, Positive symptom total, posttraumatic stress disorder, posttraumatic stress disorder checklist, Proximal Traumatic Exposure, psychological distress, psychosis, PTSD, questionnaire, receiver operating characteristic, Security, security professionals, self report, sociodemographics, trauma exposure
@article{antonioLatentClassesProximal2026,
title = {Latent Classes of Proximal Traumatic Exposure Among Portuguese Police and Security Professionals: Associations with PTSD Symptoms and Psychological Distress},
author = {H. António and S. Albuquerque and M. Vieira de Castro and S. Bouchard and P. Gamito and R. J. Pinto},
url = {https://www.scopus.com/pages/publications/105048524559?origin=resultslist},
doi = {10.3390/psychiatryint7040173},
issn = {26735318 (ISSN)},
year = {2026},
date = {2026-01-01},
journal = {Psychiatry International},
volume = {7},
number = {4},
publisher = {Multidisciplinary Digital Publishing Institute (MDPI)},
abstract = {Background: Police and security professionals are routinely exposed to potentially traumatic events as part of occupational duties, placing them at increased risk for post-traumatic stress and broader psychological difficulties. This study aimed to identify latent classes of proximal traumatic exposure among Portuguese police/security professionals and examine their associations with PTSD symptoms and general psychological distress. Methods: A cross-sectional online survey was conducted with Portuguese police/security professionals (N = 644). Latent class analysis (LCA) was applied to 17 indicators of potentially traumatic events coded as directly experienced or witnessed, derived from the Life Events Checklist for DSM-5. PTSD symptoms were assessed using the PTSD Checklist for DSM-5, and general psychological distress was assessed using the Brief Symptom Inventory. Exploratory receiver operating characteristic (ROC) analyses examined whether counts of proximal traumatic events could approximate the LCA-derived classes. Results: A three-class solution was identified, comprising low proximal exposure (37.3%), moderate proximal exposure (40.7%), and high proximal/cumulative exposure (22.0%) classes. The classes reflected a graded cumulative pattern of exposure across traumatic event categories, rather than clearly distinct qualitative configurations defined by specific event types. Higher exposure classes were associated with progressively higher PTSD symptoms and psychological distress, and these associations remained significant after adjustment for sociodemographic and occupational variables. Exploratory receiver operating characteristic (ROC) analyses showed that a simple count of proximal traumatic event categories closely approximated the empirically derived class structure within the present sample. However, the resulting thresholds are sample-specific, exploratory, and should not be interpreted as validated screening cutoffs. Conclusions: Proximal traumatic exposure among police/security professionals appears to follow a graded cumulative structure associated with increased PTSD symptoms and psychological distress. The person-centered analysis provided an empirical test of whether exposure was organized according to qualitatively distinct event configurations or primarily along a cumulative gradient. In this sample, cumulative exposure burden emerged as the dominant organizing dimension. The count-based approximation requires external validation before any screening or decision-making application can be considered. © 2026 by the authors.},
keywords = {adult, Anxiety, article, cross-sectional study, decision making, Depression, DSM-5, female, Global Severity Index, hostility, human, human experiment, Latent Class Analysis, LEC-5, major clinical study, male, paranoia, phobia, police, Positive symptom distress index, Positive symptom total, posttraumatic stress disorder, posttraumatic stress disorder checklist, Proximal Traumatic Exposure, psychological distress, psychosis, PTSD, questionnaire, receiver operating characteristic, Security, security professionals, self report, sociodemographics, trauma exposure},
pubstate = {published},
tppubtype = {article}
}
Background: Police and security professionals are routinely exposed to potentially traumatic events as part of occupational duties, placing them at increased risk for post-traumatic stress and broader psychological difficulties. This study aimed to identify latent classes of proximal traumatic exposure among Portuguese police/security professionals and examine their associations with PTSD symptoms and general psychological distress. Methods: A cross-sectional online survey was conducted with Portuguese police/security professionals (N = 644). Latent class analysis (LCA) was applied to 17 indicators of potentially traumatic events coded as directly experienced or witnessed, derived from the Life Events Checklist for DSM-5. PTSD symptoms were assessed using the PTSD Checklist for DSM-5, and general psychological distress was assessed using the Brief Symptom Inventory. Exploratory receiver operating characteristic (ROC) analyses examined whether counts of proximal traumatic events could approximate the LCA-derived classes. Results: A three-class solution was identified, comprising low proximal exposure (37.3%), moderate proximal exposure (40.7%), and high proximal/cumulative exposure (22.0%) classes. The classes reflected a graded cumulative pattern of exposure across traumatic event categories, rather than clearly distinct qualitative configurations defined by specific event types. Higher exposure classes were associated with progressively higher PTSD symptoms and psychological distress, and these associations remained significant after adjustment for sociodemographic and occupational variables. Exploratory receiver operating characteristic (ROC) analyses showed that a simple count of proximal traumatic event categories closely approximated the empirically derived class structure within the present sample. However, the resulting thresholds are sample-specific, exploratory, and should not be interpreted as validated screening cutoffs. Conclusions: Proximal traumatic exposure among police/security professionals appears to follow a graded cumulative structure associated with increased PTSD symptoms and psychological distress. The person-centered analysis provided an empirical test of whether exposure was organized according to qualitatively distinct event configurations or primarily along a cumulative gradient. In this sample, cumulative exposure burden emerged as the dominant organizing dimension. The count-based approximation requires external validation before any screening or decision-making application can be considered. © 2026 by the authors.
2.
Zoungrana, A. F.; Moudoud, H.; Tajeuna, E. G.; Adi, K.
Adversarial Ensemble Framework: Leveraging GANs for Robust Intrusion Detection in IoT Networks Proceedings Article
In: K., Adi; O., Nguena Timo; N., Boulahia-Cuppens; D., Espes; N., Stakhanova; M., Omar (Ed.): Lect. Notes Comput. Sci., pp. 85–99, Springer Science and Business Media Deutschland GmbH, 2026, ISBN: 03029743 (ISSN); 978-303220731-9 (ISBN), (Journal Abbreviation: Lect. Notes Comput. Sci.).
Abstract | Links | BibTeX | Tags: Adversarial networks, Class imbalance, Computer crime, Concept drifts, Gallium nitride, Generative adversarial networks, Internet of thing network, Internet of things, Intrusion Detection, Intrusion Detection Systems, Intrusion-Detection, IoT Networks, Key Issues, Network intrusion, Network security, Rapid expansion, Security, Security challenges
@inproceedings{zoungranaAdversarialEnsembleFramework2026,
title = {Adversarial Ensemble Framework: Leveraging GANs for Robust Intrusion Detection in IoT Networks},
author = {A. F. Zoungrana and H. Moudoud and E. G. Tajeuna and K. Adi},
editor = {Adi K. and Nguena Timo O. and Boulahia-Cuppens N. and Espes D. and Stakhanova N. and Omar M.},
url = {https://www.scopus.com/pages/publications/105046136116?origin=resultslist},
doi = {10.1007/978-3-032-20732-6_6},
isbn = {03029743 (ISSN); 978-303220731-9 (ISBN)},
year = {2026},
date = {2026-01-01},
booktitle = {Lect. Notes Comput. Sci.},
volume = {16295 LNCS},
pages = {85–99},
publisher = {Springer Science and Business Media Deutschland GmbH},
abstract = {The rapid expansion of Internet of Things (IoT) devices introduces complex security challenges that traditional intrusion detection systems struggle to address. This paper proposes an Adversarial Ensemble Framework using Generative Adversarial Networks (GANs) to improve the accuracy and resilience of intrusion detection in IoT environments. The framework tackles key issues such as class imbalance, concept drift, and adversarial attacks by employing multiple GAN variants such as Vanilla GAN, Conditional GAN (CGAN), and Wasserstein GAN (WGAN) to generate high-quality synthetic attack data. A dynamic ensemble learning mechanism selects the most effective model for each attack type based on performance metrics. Experiments on NSL-KDD and CIC-IDS2017 show that WGAN yields the most effective synthetic data, contributing to a detection rate of up to 96%. The approach proves particularly effective in identifying rare attacks, making it a scalable and adaptive solution for IoT security. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.},
note = {Journal Abbreviation: Lect. Notes Comput. Sci.},
keywords = {Adversarial networks, Class imbalance, Computer crime, Concept drifts, Gallium nitride, Generative adversarial networks, Internet of thing network, Internet of things, Intrusion Detection, Intrusion Detection Systems, Intrusion-Detection, IoT Networks, Key Issues, Network intrusion, Network security, Rapid expansion, Security, Security challenges},
pubstate = {published},
tppubtype = {inproceedings}
}
The rapid expansion of Internet of Things (IoT) devices introduces complex security challenges that traditional intrusion detection systems struggle to address. This paper proposes an Adversarial Ensemble Framework using Generative Adversarial Networks (GANs) to improve the accuracy and resilience of intrusion detection in IoT environments. The framework tackles key issues such as class imbalance, concept drift, and adversarial attacks by employing multiple GAN variants such as Vanilla GAN, Conditional GAN (CGAN), and Wasserstein GAN (WGAN) to generate high-quality synthetic attack data. A dynamic ensemble learning mechanism selects the most effective model for each attack type based on performance metrics. Experiments on NSL-KDD and CIC-IDS2017 show that WGAN yields the most effective synthetic data, contributing to a detection rate of up to 96%. The approach proves particularly effective in identifying rare attacks, making it a scalable and adaptive solution for IoT security. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.
3.
Mehrban, A.; Houda, Z. A. El; Moudoud, H.; Brik, B.; Khoukhi, L.
Securing O-RAN Equipment Using Blockchain-Based Supply Chain Verification Proceedings Article
In: Int. Wirel. Commun. Mob. Comput. Conf., IWCMC, pp. 1570–1575, Institute of Electrical and Electronics Engineers Inc., 2025, ISBN: 979-833150887-6 (ISBN), (Journal Abbreviation: Int. Wirel. Commun. Mob. Comput. Conf., IWCMC).
Abstract | Links | BibTeX | Tags: Access network equipment, Authentication, Block-chain, Blockchain, Cryptography, Denial-of-service attack, Firmware, Firmware authentication, Multi-vendor, Network architecture, Network security, O-RAN, Open radio access network, Radio access networks, Security, Security systems, Security vulnerabilities, Supply Chain Verification, Supply chains, Telecommunications networks
@inproceedings{mehrbanSecuringORANEquipment2025,
title = {Securing O-RAN Equipment Using Blockchain-Based Supply Chain Verification},
author = {A. Mehrban and Z. A. El Houda and H. Moudoud and B. Brik and L. Khoukhi},
url = {https://www.scopus.com/pages/publications/105011364438?origin=resultslist},
doi = {10.1109/IWCMC65282.2025.11059692},
isbn = {979-833150887-6 (ISBN)},
year = {2025},
date = {2025-01-01},
booktitle = {Int. Wirel. Commun. Mob. Comput. Conf., IWCMC},
pages = {1570–1575},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {The Open Radio Access Network (O-RAN) architecture has enabled the integration of multi-vendor equipment, yielding a significant enhancement in the flexibility and interoperability of telecommunications networks. However, this openness has also introduced new security vulnerabilities, particularly in supply chain integrity. Malicious actors may exploit weaknesses at various stages of production, distribution, or integration, leading to critical threats such as data tampering, unauthorized access, and denial-of-service (DOS) attacks. To address these challenges, this paper proposes a novel blockchain-based framework designed to secure the O-RAN supply chain. The proposed solution leverages a private permissioned blockchain ledger and cryptographic firmware authentication to ensure the integrity and authenticity of network equipment throughout its lifecycle. Specifically, the framework consists of: (1) a decentralized architecture integrating blockchain network components, equipment node validators, and secure firmware authentication mechanisms; and (2) a consensus-based verification model to enhance trust and transparency within the supply chain. To the best of our knowledge, this is one of the first approaches to use blockchain for O-RAN supply chain security, and also addressing emerging security threats in a scalable and tamper-resistant manner. Experimental validation and security assessments demonstrate the effectiveness of the proposed framework in mitigating supply chain risks, making it a promising solution for ensuring trust and robustness in next-generation O-RAN ecosystems. © 2025 IEEE.},
note = {Journal Abbreviation: Int. Wirel. Commun. Mob. Comput. Conf., IWCMC},
keywords = {Access network equipment, Authentication, Block-chain, Blockchain, Cryptography, Denial-of-service attack, Firmware, Firmware authentication, Multi-vendor, Network architecture, Network security, O-RAN, Open radio access network, Radio access networks, Security, Security systems, Security vulnerabilities, Supply Chain Verification, Supply chains, Telecommunications networks},
pubstate = {published},
tppubtype = {inproceedings}
}
The Open Radio Access Network (O-RAN) architecture has enabled the integration of multi-vendor equipment, yielding a significant enhancement in the flexibility and interoperability of telecommunications networks. However, this openness has also introduced new security vulnerabilities, particularly in supply chain integrity. Malicious actors may exploit weaknesses at various stages of production, distribution, or integration, leading to critical threats such as data tampering, unauthorized access, and denial-of-service (DOS) attacks. To address these challenges, this paper proposes a novel blockchain-based framework designed to secure the O-RAN supply chain. The proposed solution leverages a private permissioned blockchain ledger and cryptographic firmware authentication to ensure the integrity and authenticity of network equipment throughout its lifecycle. Specifically, the framework consists of: (1) a decentralized architecture integrating blockchain network components, equipment node validators, and secure firmware authentication mechanisms; and (2) a consensus-based verification model to enhance trust and transparency within the supply chain. To the best of our knowledge, this is one of the first approaches to use blockchain for O-RAN supply chain security, and also addressing emerging security threats in a scalable and tamper-resistant manner. Experimental validation and security assessments demonstrate the effectiveness of the proposed framework in mitigating supply chain risks, making it a promising solution for ensuring trust and robustness in next-generation O-RAN ecosystems. © 2025 IEEE.
4.
Mehrban, A.; Houda, Z. A. El; Moudoud, H.; Brik, B.; Khoukhi, L.
A Blockchain-Enabled Multi-Layered Zero-Trust Security Framework for O-RAN Proceedings Article
In: Int. Wirel. Commun. Mob. Comput. Conf., IWCMC, pp. 1564–1569, Institute of Electrical and Electronics Engineers Inc., 2025, ISBN: 979-833150887-6 (ISBN), (Journal Abbreviation: Int. Wirel. Commun. Mob. Comput. Conf., IWCMC).
Abstract | Links | BibTeX | Tags: Access control, Block-chain, Blockchain, Data privacy, Federated learning, federated learning (FL), Internet of thing, Internet of things, Internet of Things (IoT), Interoperability, Learning systems, Mobile telecommunication systems, Multi-layered, Network architecture, Network security, Open access, Open radio access network, open radio access network (O-RAN), Radio, Radio access networks, Radio access technologies, Radio communication, Secure communication, Security, Security frameworks, Security risks, Transfer learning, Trusted computing
@inproceedings{mehrbanBlockchainEnabledMultiLayeredZeroTrust2025,
title = {A Blockchain-Enabled Multi-Layered Zero-Trust Security Framework for O-RAN},
author = {A. Mehrban and Z. A. El Houda and H. Moudoud and B. Brik and L. Khoukhi},
url = {https://www.scopus.com/pages/publications/105011345211?origin=resultslist},
doi = {10.1109/IWCMC65282.2025.11059720},
isbn = {979-833150887-6 (ISBN)},
year = {2025},
date = {2025-01-01},
booktitle = {Int. Wirel. Commun. Mob. Comput. Conf., IWCMC},
pages = {1564–1569},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {O-RAN (Open Radio Access Network) is a set of open and interoperable radio access technologies, guided by the O-RAN Alliance, that, despite an open ecosystem, introduces significant security risks, expanding the threat surface in 6G networks. Traditional perimeter-based security approaches are inadequate for O-RAN's highly distributed, multi-vendor environments, where Zero Trust Architecture (ZTA) becomes essential for robust security. To address these challenges, we propose a novel blockchain-based, decentralized Zero-Trust Framework specifically designed for O-RAN security. Our proposed framework comprises two key layers: the first layer utilizes Federated Learning (FL) and Transfer Learning (TL) for advanced attack detection, enabling distributed, privacy-preserving threat analysis across O-RAN nodes. The second layer enforces Zero Trust access control through a blockchain-based identity management system, ensuring tamper-resistant, real-time policy updates. This multi-layered framework provides adaptive threat detection and resilient access control, validated through simulations demonstrating high detection accuracy and robust access management with minimal impact on network performance, offering a scalable security solution for next-generation O-RAN deployments. © 2025 IEEE.},
note = {Journal Abbreviation: Int. Wirel. Commun. Mob. Comput. Conf., IWCMC},
keywords = {Access control, Block-chain, Blockchain, Data privacy, Federated learning, federated learning (FL), Internet of thing, Internet of things, Internet of Things (IoT), Interoperability, Learning systems, Mobile telecommunication systems, Multi-layered, Network architecture, Network security, Open access, Open radio access network, open radio access network (O-RAN), Radio, Radio access networks, Radio access technologies, Radio communication, Secure communication, Security, Security frameworks, Security risks, Transfer learning, Trusted computing},
pubstate = {published},
tppubtype = {inproceedings}
}
O-RAN (Open Radio Access Network) is a set of open and interoperable radio access technologies, guided by the O-RAN Alliance, that, despite an open ecosystem, introduces significant security risks, expanding the threat surface in 6G networks. Traditional perimeter-based security approaches are inadequate for O-RAN's highly distributed, multi-vendor environments, where Zero Trust Architecture (ZTA) becomes essential for robust security. To address these challenges, we propose a novel blockchain-based, decentralized Zero-Trust Framework specifically designed for O-RAN security. Our proposed framework comprises two key layers: the first layer utilizes Federated Learning (FL) and Transfer Learning (TL) for advanced attack detection, enabling distributed, privacy-preserving threat analysis across O-RAN nodes. The second layer enforces Zero Trust access control through a blockchain-based identity management system, ensuring tamper-resistant, real-time policy updates. This multi-layered framework provides adaptive threat detection and resilient access control, validated through simulations demonstrating high detection accuracy and robust access management with minimal impact on network performance, offering a scalable security solution for next-generation O-RAN deployments. © 2025 IEEE.
5.
Moudoud, H.; Houda, Z. A. El; Brik, B.; Jan, M. A.; Alshawi, B.
Advancing Robustness and Privacy in Federated Learning for Secure Autonomous Vehicle Systems Journal Article
In: IEEE Transactions on Consumer Electronics, vol. 71, no. 2, pp. 6183–6192, 2025, ISSN: 00983063 (ISSN).
Abstract | Links | BibTeX | Tags: Augmented intelligence of things, Autonomous driving, Autonomous vehicle system, Autonomous Vehicles, Critical challenges, Differential privacy, Distributed machine learning, Driving environment, Federated learning, Privacy, Security, Security and privacy, Vehicle system
@article{moudoudAdvancingRobustnessPrivacy2025,
title = {Advancing Robustness and Privacy in Federated Learning for Secure Autonomous Vehicle Systems},
author = {H. Moudoud and Z. A. El Houda and B. Brik and M. A. Jan and B. Alshawi},
url = {https://www.scopus.com/pages/publications/105002620945?origin=resultslist},
doi = {10.1109/TCE.2025.3558999},
issn = {00983063 (ISSN)},
year = {2025},
date = {2025-01-01},
journal = {IEEE Transactions on Consumer Electronics},
volume = {71},
number = {2},
pages = {6183–6192},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {The rapid development of Autonomous Vehicle Systems (AVS) is transforming transportation, enabling safer, more efficient mobility. However, ensuring the security and privacy of sensitive data generated by AVS remains a major challenge. Federated Learning (FL) has emerged as a promising solution for AVS by enabling distributed machine learning across connected vehicles without sharing raw data, thereby enhancing privacy. Despite these advantages, FL faces critical challenges in autonomous driving environments, including high communication overhead, latency, and vulnerability to adversarial attacks. To address these challenges, we propose SecureFL, a novel framework designed to enhance the robustness and privacy of FL in autonomous vehicle systems. First, we propose a Federated Gradient Sign Attack (FGSA) detection mechanism using an ensemble of classifiers to identify and mitigate adversarial attacks that attempt to corrupt the global learning model. Then, we integrate a Graph Neural Network (GNN)-based reputation system that evaluates the reliability of vehicles based on data quality, prioritizing contributions from trustworthy sources, and dynamically adjusting participation in the FL process. Finally, we introduce an uplink scheduling mechanism utilizing a rate-splitting multiple access (RSMA) technique to optimize data transmission and reduce latency, ensuring efficient communication across the AVS network. The framework’s effectiveness is validated through simulations in real-world AVS environments, demonstrating SecureFL’s capability to strengthen security, privacy, and communication efficiency in federated learning for autonomous vehicles. This work contributes to advancing the robustness and privacy of FL, enabling safer and more secure autonomous driving. © 1975-2011 IEEE.},
keywords = {Augmented intelligence of things, Autonomous driving, Autonomous vehicle system, Autonomous Vehicles, Critical challenges, Differential privacy, Distributed machine learning, Driving environment, Federated learning, Privacy, Security, Security and privacy, Vehicle system},
pubstate = {published},
tppubtype = {article}
}
The rapid development of Autonomous Vehicle Systems (AVS) is transforming transportation, enabling safer, more efficient mobility. However, ensuring the security and privacy of sensitive data generated by AVS remains a major challenge. Federated Learning (FL) has emerged as a promising solution for AVS by enabling distributed machine learning across connected vehicles without sharing raw data, thereby enhancing privacy. Despite these advantages, FL faces critical challenges in autonomous driving environments, including high communication overhead, latency, and vulnerability to adversarial attacks. To address these challenges, we propose SecureFL, a novel framework designed to enhance the robustness and privacy of FL in autonomous vehicle systems. First, we propose a Federated Gradient Sign Attack (FGSA) detection mechanism using an ensemble of classifiers to identify and mitigate adversarial attacks that attempt to corrupt the global learning model. Then, we integrate a Graph Neural Network (GNN)-based reputation system that evaluates the reliability of vehicles based on data quality, prioritizing contributions from trustworthy sources, and dynamically adjusting participation in the FL process. Finally, we introduce an uplink scheduling mechanism utilizing a rate-splitting multiple access (RSMA) technique to optimize data transmission and reduce latency, ensuring efficient communication across the AVS network. The framework’s effectiveness is validated through simulations in real-world AVS environments, demonstrating SecureFL’s capability to strengthen security, privacy, and communication efficiency in federated learning for autonomous vehicles. This work contributes to advancing the robustness and privacy of FL, enabling safer and more secure autonomous driving. © 1975-2011 IEEE.
6.
Davoust, A.; Gagnon, F.; Esfandiari, B.; Kunz, T.; Cormier, A.
Towards Securing Peer-to-Peer SIP in the MANET Context: Existing Work and Perspectives Proceedings Article
In: Y., Georgalas N. Min G. Wu (Ed.): Proceedings - 2017 IEEE International Conference on Internet of Things, IEEE Green Computing and Communications, IEEE Cyber, Physical and Social Computing, IEEE Smart Data, iThings-GreenCom-CPSCom-SmartData 2017, pp. 223–229, Institute of Electrical and Electronics Engineers Inc., 2017, ISBN: 978-1-5386-3065-5.
Abstract | Links | BibTeX | Tags: Ad-hoc networks, Building blockes, Instant messaging, Internet protocols, Mobile ad-hoc networks, Mobile telecommunication systems, Network contexts, Network security, P2P, Peer to peer networks, Peer-to-peer session initiation protocols, Radio links, Security, Session Initiation Protocols, Social applications, Vehicular ad hoc networks
@inproceedings{davoust_towards_2017,
title = {Towards Securing Peer-to-Peer SIP in the MANET Context: Existing Work and Perspectives},
author = {A. Davoust and F. Gagnon and B. Esfandiari and T. Kunz and A. Cormier},
editor = {Georgalas N. Min G. Wu Y.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85047394150&doi=10.1109%2fiThings-GreenCom-CPSCom-SmartData.2017.38&partnerID=40&md5=738bee95270122e76104e7afc52fe946},
doi = {10.1109/iThings-GreenCom-CPSCom-SmartData.2017.38},
isbn = {978-1-5386-3065-5},
year = {2017},
date = {2017-01-01},
booktitle = {Proceedings - 2017 IEEE International Conference on Internet of Things, IEEE Green Computing and Communications, IEEE Cyber, Physical and Social Computing, IEEE Smart Data, iThings-GreenCom-CPSCom-SmartData 2017},
volume = {2018-January},
pages = {223–229},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {The Session Initiation Protocol (SIP) is a key building block of many social applications, including VoIP communication and instant messaging. In its original architecture, SIP heavily relies on servers such as proxies and registrars. Mobile Ad hoc NETworks (MANETs) are networks comprised of mobile devices that communicate over wireless links, such as tactical radio networks or vehicular networks. In such networks, no fixed infrastructure exists and server-based solutions need to be redesigned to work in a peer-to-peer fashion. We survey existing proposals for the implementation of SIP over such MANETs and analyze their security issues. We then discuss potential solutions and their suitability in the MANET context. © 2017 IEEE.},
keywords = {Ad-hoc networks, Building blockes, Instant messaging, Internet protocols, Mobile ad-hoc networks, Mobile telecommunication systems, Network contexts, Network security, P2P, Peer to peer networks, Peer-to-peer session initiation protocols, Radio links, Security, Session Initiation Protocols, Social applications, Vehicular ad hoc networks},
pubstate = {published},
tppubtype = {inproceedings}
}
The Session Initiation Protocol (SIP) is a key building block of many social applications, including VoIP communication and instant messaging. In its original architecture, SIP heavily relies on servers such as proxies and registrars. Mobile Ad hoc NETworks (MANETs) are networks comprised of mobile devices that communicate over wireless links, such as tactical radio networks or vehicular networks. In such networks, no fixed infrastructure exists and server-based solutions need to be redesigned to work in a peer-to-peer fashion. We survey existing proposals for the implementation of SIP over such MANETs and analyze their security issues. We then discuss potential solutions and their suitability in the MANET context. © 2017 IEEE.
7.
Davoust, A.; Gagnon, F.; Esfandiari, B.; Kunz, T.; Cormier, A.
Towards Securing Peer-to-Peer SIP in the MANET Context: Existing Work and Perspectives Proceedings Article
In: Y., Georgalas N. Min G. Wu (Ed.): Proceedings - 2017 IEEE International Conference on Internet of Things, IEEE Green Computing and Communications, IEEE Cyber, Physical and Social Computing, IEEE Smart Data, iThings-GreenCom-CPSCom-SmartData 2017, pp. 223–229, Institute of Electrical and Electronics Engineers Inc., 2017, ISBN: 978-1-5386-3065-5.
Abstract | Links | BibTeX | Tags: Ad-hoc networks, Building blockes, Instant messaging, Internet protocols, Mobile ad-hoc networks, Mobile telecommunication systems, Network contexts, Network security, P2P, Peer to peer networks, Peer-to-peer session initiation protocols, Radio links, Security, Session Initiation Protocols, Social applications, Vehicular ad hoc networks
@inproceedings{davoustSecuringPeertoPeerSIP2017,
title = {Towards Securing Peer-to-Peer SIP in the MANET Context: Existing Work and Perspectives},
author = {A. Davoust and F. Gagnon and B. Esfandiari and T. Kunz and A. Cormier},
editor = {Georgalas N. Min G. Wu Y.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85047394150&doi=10.1109%2fiThings-GreenCom-CPSCom-SmartData.2017.38&partnerID=40&md5=738bee95270122e76104e7afc52fe946},
doi = {10.1109/iThings-GreenCom-CPSCom-SmartData.2017.38},
isbn = {978-1-5386-3065-5},
year = {2017},
date = {2017-01-01},
booktitle = {Proceedings - 2017 IEEE International Conference on Internet of Things, IEEE Green Computing and Communications, IEEE Cyber, Physical and Social Computing, IEEE Smart Data, iThings-GreenCom-CPSCom-SmartData 2017},
volume = {2018-January},
pages = {223–229},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {The Session Initiation Protocol (SIP) is a key building block of many social applications, including VoIP communication and instant messaging. In its original architecture, SIP heavily relies on servers such as proxies and registrars. Mobile Ad hoc NETworks (MANETs) are networks comprised of mobile devices that communicate over wireless links, such as tactical radio networks or vehicular networks. In such networks, no fixed infrastructure exists and server-based solutions need to be redesigned to work in a peer-to-peer fashion. We survey existing proposals for the implementation of SIP over such MANETs and analyze their security issues. We then discuss potential solutions and their suitability in the MANET context. © 2017 IEEE.},
keywords = {Ad-hoc networks, Building blockes, Instant messaging, Internet protocols, Mobile ad-hoc networks, Mobile telecommunication systems, Network contexts, Network security, P2P, Peer to peer networks, Peer-to-peer session initiation protocols, Radio links, Security, Session Initiation Protocols, Social applications, Vehicular ad hoc networks},
pubstate = {published},
tppubtype = {inproceedings}
}
The Session Initiation Protocol (SIP) is a key building block of many social applications, including VoIP communication and instant messaging. In its original architecture, SIP heavily relies on servers such as proxies and registrars. Mobile Ad hoc NETworks (MANETs) are networks comprised of mobile devices that communicate over wireless links, such as tactical radio networks or vehicular networks. In such networks, no fixed infrastructure exists and server-based solutions need to be redesigned to work in a peer-to-peer fashion. We survey existing proposals for the implementation of SIP over such MANETs and analyze their security issues. We then discuss potential solutions and their suitability in the MANET context. © 2017 IEEE.