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<p>One of the most important and dangerous attacks on the blockchain is a splitting attack when an attacker manages to build an alternative chain of blocks of the largest possible length. The article proposes a new model for implementing such an attack and defines the main rules for its implementation, such as under what conditions attackers start creating branches and to which branch they add a new block. In this case, a standard approach is used to determine the behavior of honest slot leaders where they always add new blocks to a longer branch and in the case of a fork, or two branches of the same length they can choose any of them. A fast simulation modeling method is proposed, which allows estimating the probability that the fork length will reach a certain value. This method is based on the combined use of both elements of the Monte Carlo method and implanted recurrent formulas. To verify the correctness of the proposed method, a comparison of the estimates obtained by this method and the standard Monte Carlo method was carried out on numerical examples. Depending on the estimated probability, the fast simulation modeling method provides a time gain of several orders of magnitude.</p>

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Fast Simulating of a Strategy for a Splitting Attack on a Blockchain Based on the Proof-of-Stake Consensus Protocol

  • 期刊论文

  • 发表日期：

    2026年1月1日

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  • L. V. Kovalchuk,
  • I. M. Kuznetsov,
  • M. Yu. Kuznetsov

摘要

One of the most important and dangerous attacks on the blockchain is a splitting attack when an attacker manages to build an alternative chain of blocks of the largest possible length. The article proposes a new model for implementing such an attack and defines the main rules for its implementation, such as under what conditions attackers start creating branches and to which branch they add a new block. In this case, a standard approach is used to determine the behavior of honest slot leaders where they always add new blocks to a longer branch and in the case of a fork, or two branches of the same length they can choose any of them. A fast simulation modeling method is proposed, which allows estimating the probability that the fork length will reach a certain value. This method is based on the combined use of both elements of the Monte Carlo method and implanted recurrent formulas. To verify the correctness of the proposed method, a comparison of the estimates obtained by this method and the standard Monte Carlo method was carried out on numerical examples. Depending on the estimated probability, the fast simulation modeling method provides a time gain of several orders of magnitude.