Slide
Centre Interdisciplinaire
de Recherche et d’Innovation
en Cybersécurité et Société
de Recherche et d’Innovation
en Cybersécurité et Société
1.
Amari, H.; Houda, Z. A. El; Moudoud, H.; Khoukhi, L.; Belguith, L. H.
Blockchain-Based Federated Learning for Enhanced Cyber-Threats Detection in Connected Vehicles Article d'actes
Dans: M., Valenti; D., Reed; M., Torres (Ed.): IEEE Int Conf Commun, p. 4257–4262, Institute of Electrical and Electronics Engineers Inc., 2025, ISBN: 15503607 (ISSN); 979-833150521-9 (ISBN), (Journal Abbreviation: IEEE Int Conf Commun).
Résumé | Liens | BibTeX | Étiquettes: Block-chain, Blockchain, Central layers, Computer crime, Connected vehicle, Connected Vehicles, Cyber threats, Cyberthreat detection, Cyberthreats, Cyberthreats Detection, Data privacy, Federated learning, Intelligent transport, Intelligent vehicle highway systems, Internet of things, Intrusion Detection, Intrusion Detection Systems, Learning systems, Network security, SDN, Threat detection, Traffic control, Vehicles
@inproceedings{amariBlockchainBasedFederatedLearning2025,
title = {Blockchain-Based Federated Learning for Enhanced Cyber-Threats Detection in Connected Vehicles},
author = {H. Amari and Z. A. El Houda and H. Moudoud and L. Khoukhi and L. H. Belguith},
editor = {Valenti M. and Reed D. and Torres M.},
url = {https://www.scopus.com/pages/publications/105018456633?origin=resultslist},
doi = {10.1109/ICC52391.2025.11161266},
isbn = {15503607 (ISSN); 979-833150521-9 (ISBN)},
year = {2025},
date = {2025-01-01},
booktitle = {IEEE Int Conf Commun},
pages = {4257–4262},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {Over the past few years, there have been made significant strides in advancing the Internet of Vehicles (IoV), recognizing its strategic importance in Intelligent Transport Systems. The proliferation of connected and autonomous vehicles on the roads has propelled the IoV into the spotlight. However, addressing the specific demands of vehicular networks, such as low latency, high mobility, extensive connectivity of 5G/6G networks, and robust security, remains a substantial challenge. Therefore, there is a critical need for substantial progress in implementing a resilient Intrusion Detection System within the IoV ecosystem. This paper introduces VFed-IDS, a decentralized, secure, flexible, scalable, and robust Blockchain and Federated Learning-based intrusion detection system. VFed-IDS is designed to identify cyber threats in the IoV while preserving privacy in connected vehicles. The proposed architecture consists of three main layers: the central layer, the local layer, and the Blockchain layer. The central layer includes the SDN Controller, responsible for training and aggregating the global model. The local layer comprises vehicles training individual models based on their private local datasets. The Blockchain layer introduces the Smart Contract VFed-SC, which manages the list of authenticated and collaborating vehicles in the Federated Learning process. It also hashes trained local model updates before transmitting them as transactions between the central and local layers. Simulation results demonstrate that VFed-IDS achieves a high accuracy rate of 99%, effectively enhancing the autonomous behavior of connected vehicles against cyber threats. © 2025 IEEE.},
note = {Journal Abbreviation: IEEE Int Conf Commun},
keywords = {Block-chain, Blockchain, Central layers, Computer crime, Connected vehicle, Connected Vehicles, Cyber threats, Cyberthreat detection, Cyberthreats, Cyberthreats Detection, Data privacy, Federated learning, Intelligent transport, Intelligent vehicle highway systems, Internet of things, Intrusion Detection, Intrusion Detection Systems, Learning systems, Network security, SDN, Threat detection, Traffic control, Vehicles},
pubstate = {published},
tppubtype = {inproceedings}
}
Over the past few years, there have been made significant strides in advancing the Internet of Vehicles (IoV), recognizing its strategic importance in Intelligent Transport Systems. The proliferation of connected and autonomous vehicles on the roads has propelled the IoV into the spotlight. However, addressing the specific demands of vehicular networks, such as low latency, high mobility, extensive connectivity of 5G/6G networks, and robust security, remains a substantial challenge. Therefore, there is a critical need for substantial progress in implementing a resilient Intrusion Detection System within the IoV ecosystem. This paper introduces VFed-IDS, a decentralized, secure, flexible, scalable, and robust Blockchain and Federated Learning-based intrusion detection system. VFed-IDS is designed to identify cyber threats in the IoV while preserving privacy in connected vehicles. The proposed architecture consists of three main layers: the central layer, the local layer, and the Blockchain layer. The central layer includes the SDN Controller, responsible for training and aggregating the global model. The local layer comprises vehicles training individual models based on their private local datasets. The Blockchain layer introduces the Smart Contract VFed-SC, which manages the list of authenticated and collaborating vehicles in the Federated Learning process. It also hashes trained local model updates before transmitting them as transactions between the central and local layers. Simulation results demonstrate that VFed-IDS achieves a high accuracy rate of 99%, effectively enhancing the autonomous behavior of connected vehicles against cyber threats. © 2025 IEEE.
2.
Moudoud, H.; Houda, Z. A. El; Brik, B.
A Blockchain-Based Cross-Domain DDoS Mitigation in Consumer Networks Article de journal
Dans: IEEE Transactions on Consumer Electronics, vol. 71, no 2, p. 7095–7104, 2025, ISSN: 00983063 (ISSN).
Résumé | Liens | BibTeX | Étiquettes: Block-chain, Blockchain, Consumer network, Denial-of-service attack, digital twins, Distributed denial of service, Edge Computing, Fuzzy logic, Fuzzy-Logic, Inter-domain, Internet service providers, Network function virtualization, Network functions, NFV, Platform as a Service (PaaS), Resources sharing, SDN, Software-defined networkings, Virtualizations
@article{moudoudBlockchainBasedCrossDomainDDoS2025,
title = {A Blockchain-Based Cross-Domain DDoS Mitigation in Consumer Networks},
author = {H. Moudoud and Z. A. El Houda and B. Brik},
url = {https://www.scopus.com/pages/publications/105002613162?origin=resultslist},
doi = {10.1109/TCE.2025.3559451},
issn = {00983063 (ISSN)},
year = {2025},
date = {2025-01-01},
journal = {IEEE Transactions on Consumer Electronics},
volume = {71},
number = {2},
pages = {7095–7104},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {Distributed Denial of Service (DDoS) attacks pose significant threats to the availability and security of consumer networks and Internet service providers (ISPs). This is a significant concern due to the potential vulnerabilities and security risks associated with the rapid increase in the number of insecure Internet of Things (IoT) devices. Adopting an inter-domain DDoS collaboration strategy is a promising solution to address this issue. However, manual configuration and management of resources across multiple domains can be time-consuming, error-prone, and inefficient. Moreover, the existing inter-domain DDoS mitigation mechanisms (i.e., Cooperative Defense mechanisms) are facing obstacles due to the lack of incentives for cooperation, low flexibility, and high cost. Most importantly, many of them are centralized, which risks single points of failure, hampering collaboration and resource sharing among Autonomous Systems (ASs). The new emerging techniques, such as Digital-Twin (DT) empowered by Network Function Virtualization (NFV), Software-Defined Networking (SDN), and Blockchain introduce new opportunities for efficient and flexible inter-domain DDoS collaboration i.e., resources sharing among multiple SDN-based domains. In this context, we propose SecureShare, a novel digital twin-enabled inter-domain DDoS mitigation framework that allows for an efficient, fair, and secure dynamic resource-sharing among SDN-based domains to deal with large-scale DDoS attacks through resource sharing. The deployment of SecureShare is executed within Ethereum’s test network, Sepolia. Furthermore, we performed extensive experiments employing Microsoft Azure Digital Twins (ADT), a platform-as-a-service tool for generating twin graphs of physical objects. The experimental results show that SecureShare achieves promising results in terms of efficiency, security, and flexibility. © 1975-2011 IEEE.},
keywords = {Block-chain, Blockchain, Consumer network, Denial-of-service attack, digital twins, Distributed denial of service, Edge Computing, Fuzzy logic, Fuzzy-Logic, Inter-domain, Internet service providers, Network function virtualization, Network functions, NFV, Platform as a Service (PaaS), Resources sharing, SDN, Software-defined networkings, Virtualizations},
pubstate = {published},
tppubtype = {article}
}
Distributed Denial of Service (DDoS) attacks pose significant threats to the availability and security of consumer networks and Internet service providers (ISPs). This is a significant concern due to the potential vulnerabilities and security risks associated with the rapid increase in the number of insecure Internet of Things (IoT) devices. Adopting an inter-domain DDoS collaboration strategy is a promising solution to address this issue. However, manual configuration and management of resources across multiple domains can be time-consuming, error-prone, and inefficient. Moreover, the existing inter-domain DDoS mitigation mechanisms (i.e., Cooperative Defense mechanisms) are facing obstacles due to the lack of incentives for cooperation, low flexibility, and high cost. Most importantly, many of them are centralized, which risks single points of failure, hampering collaboration and resource sharing among Autonomous Systems (ASs). The new emerging techniques, such as Digital-Twin (DT) empowered by Network Function Virtualization (NFV), Software-Defined Networking (SDN), and Blockchain introduce new opportunities for efficient and flexible inter-domain DDoS collaboration i.e., resources sharing among multiple SDN-based domains. In this context, we propose SecureShare, a novel digital twin-enabled inter-domain DDoS mitigation framework that allows for an efficient, fair, and secure dynamic resource-sharing among SDN-based domains to deal with large-scale DDoS attacks through resource sharing. The deployment of SecureShare is executed within Ethereum’s test network, Sepolia. Furthermore, we performed extensive experiments employing Microsoft Azure Digital Twins (ADT), a platform-as-a-service tool for generating twin graphs of physical objects. The experimental results show that SecureShare achieves promising results in terms of efficiency, security, and flexibility. © 1975-2011 IEEE.