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Analysis on the Block Reward of Fork After Withholding (FAW)

  • Junming Ke
  • Han JiangEmail author
  • Xiangfu Song
  • Shengnan Zhao
  • Hao Wang
  • Qiuliang Xu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11058)

Abstract

The irreversible trend in clustering of mining power raises severe concerns on stability and security of PoW based on cryptocurrency. It has been shown that, in some case, reward of a mining pool can be significantly increased by deviating honest mining strategy. As a result, many attacking strategies are proposed to maximize pools’ reward. Very recently, Kwon et. al. proposed Fork After Withholding (FAW) attack by combining selfish mining and Block Withholding (BWH) attack, which, as they stated, has a better reward than BWH. However, it is not always the case after our further investigation. In this paper, we firstly give a detailed comparation between the BWH and FAW attack, and show the implications behind them. We also consider honest mining to make the analysis of the block reward more clear. We demonstrate the imperfection of FAW in relative reward, reward after the fork and the fork state. Our main finding for FAW attack includes that the reward of victim pool increases faster compared to BWH attack, and for some cases, the attack should adopt honest mining strategy to maximize its reward, therefore, we present an improved FAW strategy, and propose a protocol for the pool’s manager to resist FAW’s attacker. Finally, we discuss the underlying flaws of FAW attack as well as countermeasures to alleviate it.

Keywords

Fork After Withholding Analysis Countermeasure 

Notes

Acknowledgments

This work is supported by the National Natural Science Foundation of China under grant No. 61572294, No. 61602287, Key Program of National Natural Science of China under grant No. 61632020, Natural Science Foundation of Shandong Province under grant No. ZR2017MF021, the Primary Research & Development Plan of Shandong Province (No. 2018GGX101037), and the Fundamental Research Funds of Shandong University under grant No. 2017JC019.

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Junming Ke
    • 1
  • Han Jiang
    • 1
    • 2
  • Xiangfu Song
    • 1
  • Shengnan Zhao
    • 1
  • Hao Wang
    • 3
  • Qiuliang Xu
    • 1
    • 2
  1. 1.School of Computer Science and TechnologyShandong UniversityJinanChina
  2. 2.School of SoftwareShandong UniversityJinanChina
  3. 3.School of Information Science and EngineeringShandong Normal UniversityJinanChina

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