Enhancing Blockchain Resilience via Multi-Signal Detection and Robust Freezing under Partitioned Networks
Received: 19 September 2025 | Revised: 12 October 2025 and 22 October 2025 | Accepted: 24 October 2025 | Online: 25 November 2025
Corresponding author: L. Naveen Kumar
Abstract
Blockchain systems, such as Bitcoin and Ethereum 2.0, face vulnerabilities under bandwidth-constrained partitions, where throughput collapses and latency increases. In addition, adversaries can exploit inconsistencies to launch double-spending attacks. This study presents a lightweight dual-layer countermeasure that integrates a robust freezing threshold ( ) with multi-signal disconnection proofs to enhance performance and security without altering consensus rules. Controlled simulation experiments on Bitcoin (PoW) and Ethereum 2.0 (PoS) show throughput gains exceeding 1000% in Ethereum and over 100% in Bitcoin, with inconsistency reduced by up to 64% and latency bounded within 5-6 blocks/s. These results confirm that attacker-aware thresholds and multi-signal validation substantially improve blockchain resilience under partitioned network conditions.
Keywords:
blockchain security, network partition, double-spending, consensus protocols, Ethereum 2.0, BitcoinDownloads
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