Secure Multicast Routing Against Collaborative Attacks in FANETs With CF-mMIMO and STAR-RIS: Blockchain and Federated Learning Design

In this article, we propose novel federated learning (FL) and blockchain-based secure multicast routing (FBSMR) protocol in flying ad hoc networks (FANETs) with cell-free massive MIMO (CF-mMIMO) and simultaneously transmitting and reflecting-reconfigurable intelligent surface (STAR-RIS) effectively avoiding collaborative attacks. The proposed FBSMR protocol integrates FL with blockchain to enhance security and prevent collaborative attacks during the routing process. Besides, by utilizing a cross-layer design, the proposed FBSMR can enhance network security and Quality-of-Service (QoS) performance. Specifically, we implement a blockchain-based approach to support secure multicast routing, which efficiently detects and isolates malicious nodes. By using these techniques, all participating nodes achieve consensus on the validity of routing paths, thereby significantly enhancing overall network security. Besides, we address the cost-minimization problem in the proposed cross-layer design by optimizing the weight values of physical layer information, data link layer information, and network layer information subject to the minimum sequence numbers, maximum end-to-end delay, and hop count constraints. To further enhance the coverage area, improve receive signal quality, and reduce the number of hops, we leverage the capabilities of STAR-RIS technology attached to the AAV (F-STAR-RIS) to refract and reflect incident waves toward desired positions, enabling significant improvements in signal quality and transmission coverage. Additionally, the FL framework is employed for real-time prediction of the secure next node, utilizing local data from each flying access point (F-AP) to predict the optimal next node, STAR-RIS configuration, and phase shift at the STAR-RIS. Simulation results demonstrate that the proposed FBSMR protocol, combined with the FedChain-based clustering protocol, establishes a more secure route against collaborative attacks and outperforms benchmark protocols in terms of connectivity, stability, and security performance.

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Publication Details

Journal
IEEE Internet of Things Journal
Published
2025-03-17
DOI
https://doi.org/10.1109/jiot.2025.3551746
Citations
4
Primary Topic
Advanced Authentication Protocols Security
Type
article
Field-Weighted Citation Impact
5.95

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article

Secure Multicast Routing Against Collaborative Attacks in FANETs With CF-mMIMO and STAR-RIS: Blockchain and Federated Learning Design

Yushintia Pramitarini, Kyusung Shim, Beongku An, Ridho Hendra Yoga Perdana
4 citations
IEEE Internet of Things Journal
Advanced Authentication Protocols Security
5.95
article

Secure Multicast Routing Against Collaborative Attacks in FANETs With CF-mMIMO and STAR-RIS: Blockchain and Federated Learning Design

Yushintia Pramitarini, Kyusung Shim, Beongku An, Ridho Hendra Yoga Perdana
article en
4 citations

Abstract

In this article, we propose novel federated learning (FL) and blockchain-based secure multicast routing (FBSMR) protocol in flying ad hoc networks (FANETs) with cell-free massive MIMO (CF-mMIMO) and simultaneously transmitting and reflecting-reconfigurable intelligent surface (STAR-RIS) effectively avoiding collaborative attacks. The proposed FBSMR protocol integrates FL with blockchain to enhance security and prevent collaborative attacks during the routing process. Besides, by utilizing a cross-layer design, the proposed FBSMR can enhance network security and Quality-of-Service (QoS) performance. Specifically, we implement a blockchain-based approach to support secure multicast routing, which efficiently detects and isolates malicious nodes. By using these techniques, all participating nodes achieve consensus on the validity of routing paths, thereby significantly enhancing overall network security. Besides, we address the cost-minimization problem in the proposed cross-layer design by optimizing the weight values of physical layer information, data link layer information, and network layer information subject to the minimum sequence numbers, maximum end-to-end delay, and hop count constraints. To further enhance the coverage area, improve receive signal quality, and reduce the number of hops, we leverage the capabilities of STAR-RIS technology attached to the AAV (F-STAR-RIS) to refract and reflect incident waves toward desired positions, enabling significant improvements in signal quality and transmission coverage. Additionally, the FL framework is employed for real-time prediction of the secure next node, utilizing local data from each flying access point (F-AP) to predict the optimal next node, STAR-RIS configuration, and phase shift at the STAR-RIS. Simulation results demonstrate that the proposed FBSMR protocol, combined with the FedChain-based clustering protocol, establishes a more secure route against collaborative attacks and outperforms benchmark protocols in terms of connectivity, stability, and security performance.

IEEE Internet of Things JournalVol. 12(12)
Hankyong National University (KR), Hongik University (KR)
National Research Foundation of Korea
Partnerships for the goals
Openalex Percentile: Top 4%
Advanced Authentication Protocols Security
5.95
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