[Paper Review] BlockSim-Net: A Network Based Blockchain Simulator

Nandini Agrawal, R Prashanthi+2 more|arXiv (Cornell University)|Nov 6, 2020

Blockchain Technology Applications and Security4 citations

TL;DR

BlockSim-Net is a high-performance, network-based blockchain simulator designed to realistically model propagation delays and distributed dynamics in proof-of-work blockchains. By simulating a decentralized network environment across multiple nodes, it enables accurate evaluation of attacks like selfish mining and defenses, outperforming single-CPU simulators such as BlockSim in capturing real-world network complexities.

ABSTRACT

Since its proposal by Eyal and Sirer (CACM '13), selfish mining attack on proof-of-work blockchains has been studied extensively in terms of both improving its impact and defending against it. Before any defense is deployed in a real world blockchain system, it needs to be tested for security and dependability. However, real blockchain systems are too complex to conduct any test on or benchmark the developed protocols. Some simulation environments have been proposed recently, such as BlockSim (Maher et al., '20). However, BlockSim is developed for the simulation of an entire network on a single CPU. Therefore, it is insufficient to capture the essence of a real blockchain network, as it is not distributed and the complications such as propagation delays that occur in reality cannot be simulated realistically enough. In this work, we propose BlockSim-Net, a simple, efficient, high performance, network-based blockchain simulator, to better reflect reality.

Motivation & Objective

• To address the limitations of existing blockchain simulators that run on a single CPU and fail to capture real network dynamics such as propagation delays.
• To develop a distributed, high-performance simulation framework that reflects the true behavior of blockchain networks in terms of latency and message propagation.
• To enable realistic testing of selfish mining attacks and defensive mechanisms before deployment in real-world blockchain systems.
• To improve the fidelity of blockchain protocol evaluation by modeling network-level complexities absent in prior simulators.

Proposed method

• BlockSim-Net is implemented as a distributed simulation framework that emulates a peer-to-peer blockchain network across multiple nodes.
• It models network propagation delays using configurable delay distributions to reflect real-world latency characteristics.
• The simulator supports pluggable consensus algorithms and attack models, including selfish mining, to evaluate protocol behavior under adversarial conditions.
• It uses event-driven simulation to efficiently manage message passing and block propagation across the network.
• The architecture allows for horizontal scaling, enabling large-scale network simulations on distributed computing resources.
• It integrates with existing blockchain protocols and supports customizable network topologies and node behaviors.

Experimental results

Research questions

• RQ1 How does the inclusion of realistic network propagation delays affect the success rate of selfish mining attacks in blockchain systems?
• RQ2 To what extent can a distributed simulation framework like BlockSim-Net better capture the dynamics of blockchain networks compared to single-CPU simulators?
• RQ3 How do different network topologies and delay distributions influence the performance and security of consensus protocols?
• RQ4 Can BlockSim-Net effectively simulate and evaluate defensive mechanisms against selfish mining attacks?

Key findings

• BlockSim-Net successfully captures network propagation delays and their impact on block propagation, which single-CPU simulators like BlockSim fail to model accurately.
• The simulator enables realistic evaluation of selfish mining attacks, showing that network delays significantly influence attack success rates.
• By simulating a distributed network environment, BlockSim-Net reveals that propagation delays can amplify the effectiveness of selfish mining beyond what is predicted by centralized models.
• The framework demonstrates high performance and scalability, supporting large-scale simulations essential for testing complex blockchain protocols.