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Open Access

REVIEW

A Comprehensive Survey on Blockchain-Enabled Techniques and Federated Learning for Secure 5G/6G Networks: Challenges, Opportunities, and Future Directions

Muhammad Asim1,*, Abdelhamied A. Ateya1, Mudasir Ahmad Wani1,2, Gauhar Ali1, Mohammed ElAffendi1, Ahmed A. Abd El-Latif1, Reshma Siyal3
1 EIAS Data Science Lab, College of Computer and Information Sciences, and Center of Excellence in Quantum and Intelligent Computing, Prince Sultan University, Riyadh, 11586, Saudi Arabia
2 College of Computer and Information Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, 11432, Saudi Arabia
3 School of Computer Science and Engineering, Central South University, Changsha, 410083, China
* Corresponding Author: Muhammad Asim. Email: email

Computers, Materials & Continua https://doi.org/10.32604/cmc.2025.070684

Received 21 July 2025; Accepted 13 November 2025; Published online 22 December 2025

Abstract

The growing developments in 5G and 6G wireless communications have revolutionized communications technologies, providing faster speeds with reduced latency and improved connectivity to users. However, it raises significant security challenges, including impersonation threats, data manipulation, distributed denial of service (DDoS) attacks, and privacy breaches. Traditional security measures are inadequate due to the decentralized and dynamic nature of next-generation networks. This survey provides a comprehensive review of how Federated Learning (FL), Blockchain, and Digital Twin (DT) technologies can collectively enhance the security of 5G and 6G systems. Blockchain offers decentralized, immutable, and transparent mechanisms for securing network transactions, while FL enables privacy-preserving collaborative learning without sharing raw data. Digital Twins create virtual replicas of network components, enabling real-time monitoring, anomaly detection, and predictive threat analysis. The survey examines major security issues in emerging wireless architectures and analyzes recent advancements that integrate FL, Blockchain, and DT to mitigate these threats. Additionally, it presents practical use cases, synthesizes key lessons learned, and identifies ongoing research challenges. Finally, the survey outlines future research directions to support the development of scalable, intelligent, and robust security frameworks for next-generation wireless networks.

Keywords

5G/6G; blockchain; federated learning; edge computing; security

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