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A Novel Data-Driven Evaluation Framework for Fork after Withholding Attack in Blockchain Systems.

Yang Zhang1,2, Yourong Chen1, Kelei Miao1

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Summary
This summary is machine-generated.

This study introduces a new framework to evaluate blockchain mining pool defenses against Fork After Withholding (FAW) attacks. The proposed system accurately assesses revenue models and optimizes computing power allocation to enhance mining pool security.

Keywords:
blockchaincomputing power allocation optimizationevaluation methodfaw attackrevenue model

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Area of Science:

  • Blockchain Technology
  • Cybersecurity
  • Network Security

Background:

  • Mining pools are crucial for blockchain revenue generation.
  • Consensus attacks, like Fork After Withholding (FAW), threaten mining pool security and efficiency.
  • Existing tools struggle to evaluate FAW attack protection capabilities.

Purpose of the Study:

  • To propose a novel evaluation framework for FAW attack protection in blockchain mining pools.
  • To establish a comprehensive revenue model for mining pools under attack scenarios.
  • To develop an efficient algorithm for computing power allocation optimization.

Main Methods:

  • Developed a revenue model including honest consensus, block withholding, successful fork revenue, and consensus cost.
  • Established distinct revenue functions for target and other mining pools.
  • Proposed an efficient computing power allocation optimization algorithm (CPAOA) using improved Aquila optimization and an artificial bee colony-inspired update mechanism.

Main Results:

  • The framework effectively evaluates the revenue of various mining pools.
  • CPAOA demonstrated rapid and accurate allocation of computing power for FAW attacks.
  • The optimization algorithm successfully avoided local optima, improving solution quality.

Conclusions:

  • The proposed framework effectively evaluates the FAW attack protection capabilities of multiple mining pools.
  • The CPAOA algorithm enhances the security of blockchain systems by optimizing defense strategies.
  • This research contributes to securing blockchain mining pools against sophisticated consensus attacks.