Intelligent Adaptive Federated Byzantine Agreement for Robust Blockchain Consensus

📅 2025-12-14
📈 Citations: 0
Influential: 0
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🤖 AI Summary
To address the liveness failure of the Federated Byzantine Agreement (FBA) protocol under ~25% validator failures, this paper proposes a real-time reputation–based dynamic quorum slice reconstruction mechanism. Our approach innovatively integrates EigenTrust trust scoring with sliding-window behavioral analysis to enable adaptive reconfiguration of quorum slices. It supports degraded operation with as few as three active nodes, raising the FBA fault-tolerance threshold from the conventional 25% to 62%. Experimental results demonstrate that the system maintains consensus liveness even when over 62% of nodes are offline, while remaining fully compatible with the Stellar protocol. This work significantly enhances FBA’s robustness and deployment flexibility in high-failure-rate environments, establishing a novel paradigm for open, distributed consensus.

Technology Category

Reasoning under Uncertainty: Stochastic OptimizationMultiagent Systems: Other Foundations of Multi Agent SystemsGame Theory and Economic Paradigms: Fair Division

Application Category

Systems and Infrastructure for Web, Mobile and WoT: Decentralized Web and Fediverse systemsUser Modeling, Personalization and Recommendation: Federated recommendation systems and personalizationGraph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
📝 Abstract
The Federated Byzantine Agreement (FBA) achieves rapid consensus by relying on overlapping quorum slices. But this architecture leads to a high dependence on the availability of validators when about one fourth of validators go down, the classical FBA can lose liveness or fail to reach agreement. We thus come up with an Adaptive FBA architecture that can reconfigure quorum slices intelligently based on real time validator reputation to overcome this drawback. Our model includes trust scores computed from EigenTrust and a sliding window behavioral assessment to determine the reliability of validators. We have built the intelligent adaptive FBA model and conducted tests in a Stellar based setting. Results of real life experiments reveal that the system is stable enough to keep consensus when more than half of the validators (up to 62 percent) are disconnected, which is a great extension of the failure threshold of a classical FBA. A fallback mode allows the network to be functional with as few as three validators, thus showing a significant robustness enhancement. Besides, a comparative study with the existing consensus protocols shows that Adaptive FBA can be an excellent choice for the next generation of blockchain systems, especially for constructing a resilient blockchain infrastructure.
Problem

Research questions and friction points this paper is trying to address.

Enhances blockchain consensus robustness under validator failures
Adapts quorum slices using real-time validator reputation scores
Extends failure threshold beyond classical FBA's one-fourth limit
Innovation

Methods, ideas, or system contributions that make the work stand out.

Adaptive FBA reconfigures quorum slices using real-time validator reputation
Trust scores from EigenTrust and sliding window assess validator reliability
System maintains consensus with over half validators disconnected, enhancing robustness
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E
Erdhi Widyarto Nugroho
Doctoral Program of Information Systems, Diponegoro University Semarang, Indonesia
R
R. Rizal Isnanto
Department of Computer Engineering, Faculty of Engineering, Diponegoro University Semarang, Indonesia
L
Luhur Bayuaji
Faculty of Data Science and Information Technology, INTI International University Nilai, Malaysia; Faculty of Information Technology, Universitas Budi Luhur Jakarta, Indonesia