Dynamic Sharding and Monte Carlo for Post-Quantum Blockchain Resilience

Abstract

Scalability and security restrictions are posing new challenges for blockchain networks, especially in the face of Distributed Denial-of-Service (DDoS) attacks and upcoming quantum threats. Previous research also found that post-quantum blockchains, despite their improved cryptographic algorithms, are still vulnerable to DDoS attacks, emphasizing the need for more resilient architectural solutions. This research studies the use of dynamic sharding, an innovative approach for post-quantum blockchains that allows for adaptive division of the network into shards based on workload and network conditions. Unlike static sharding, dynamic sharding optimizes resource allocation in real time, increasing transaction throughput and minimizing DDoS-induced disruptions. We provide a detailed study using Monte Carlo simulations to examine transaction success rates, resource consumption, and fault tolerance for both dynamic sharding-based and non-sharded post-quantum blockchains under simulated DDoS attack scenarios. The findings show that dynamic sharding leads to higher transaction success rates and more efficient resource use than non-sharded infrastructures, even in high-intensity attack scenarios. Furthermore, the combination of dynamic sharding and the Falcon post-quantum signature technique creates a layered strategy that combines cryptographic robustness, scalability, and resilience. This paper provides light on the potential of adaptive blockchain designs to address major scalability and security issues, opening the path for quantum-resilient systems.