[2602.21841] Resilient Federated Chain: Transforming Blockchain Consensus into an Active Defense Layer for Federated Learning

[2602.21841] Resilient Federated Chain: Transforming Blockchain Consensus into an Active Defense Layer for Federated Learning

arXiv - AI 4 min read Article

Summary

The paper presents the Resilient Federated Chain (RFC), a blockchain-enabled framework designed to enhance the security of Federated Learning (FL) against adversarial attacks, improving model robustness through innovative consensus mechanisms.

Why It Matters

As Federated Learning becomes integral to privacy-preserving AI, its vulnerabilities to adversarial attacks pose significant risks. The RFC framework offers a novel solution by integrating blockchain technology, potentially transforming how decentralized learning environments are secured and trusted.

Key Takeaways

  • RFC enhances resilience in Federated Learning against adversarial threats.
  • The framework repurposes blockchain consensus mechanisms for active defense.
  • Extensive evaluations show significant robustness improvements over traditional methods.
  • Adaptive defense strategies are integrated into the consensus mechanism.
  • This approach may redefine security protocols in decentralized AI systems.

Computer Science > Cryptography and Security arXiv:2602.21841 (cs) [Submitted on 25 Feb 2026] Title:Resilient Federated Chain: Transforming Blockchain Consensus into an Active Defense Layer for Federated Learning Authors:Mario García-Márquez, Nuria Rodríguez-Barroso, M.Victoria Luzón, Francisco Herrera View a PDF of the paper titled Resilient Federated Chain: Transforming Blockchain Consensus into an Active Defense Layer for Federated Learning, by Mario Garc\'ia-M\'arquez and Nuria Rodr\'iguez-Barroso and M.Victoria Luz\'on and Francisco Herrera View PDF HTML (experimental) Abstract:Federated Learning (FL) has emerged as a key paradigm for building Trustworthy AI systems by enabling privacy-preserving, decentralized model training. However, FL is highly susceptible to adversarial attacks that compromise model integrity and data confidentiality, a vulnerability exacerbated by the fact that conventional data inspection methods are incompatible with its decentralized design. While integrating FL with Blockchain technology has been proposed to address some limitations, its potential for mitigating adversarial attacks remains largely unexplored. This paper introduces Resilient Federated Chain (RFC), a novel blockchain-enabled FL framework designed specifically to enhance resilience against such threats. RFC builds upon the existing Proof of Federated Learning architecture by repurposing the redundancy of its Pooled Mining mechanism as an active defense layer that can be combine...

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