The Greedy Miner’s Dilemma: Flaws in DAG-Based Consensus Protocols

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18 Sept 2024

Abstract and I. Introduction

II. Background

III. Problem Definition

IV. DAG-Oriented Solutions

V. Game Theoretical Analysis

VI. Simulation Model

VII. Evaluation

VIII. Countermeasures

IX. Discussion and Future Work

X. Related Work

XI. Conclusion and References

XI. CONCLUSION

In this work, we started with an overview of DAG-oriented consensus protocols for Proof-of-Work blockchains, which promise to increase the transaction throughput by using random transaction selection strategy. We formulated a hypothesis that DAG protocols using the random strategy can be exploited by attackers not respecting such a strategy and instead selecting transaction based on the fees (i.e., greedy strategy), which can lead to deterioration of the overall transaction throughput. We made a game theoretical analysis of concerned DAG-oriented protocols and concluded that the random strategy, as proposed in these protocols, does not constitute a Nash equilibrium since honest players enable the greedy player to “parasite” on the system. This is contradictory result to Inclusive paper [26], which does not assume that multiple greedy miners can form a mining pool.

We conducted several experiments on simplified network topology as well as complex network using an abstracted DAG-PROTOCOL. In our experiments, we analyzed the impact of greedy miners who deviated from the modeled DAG protocol by selecting transactions based on the highest fee. We demonstrated that greedy miners have a significant advantage over honest miners in terms of profit maximization. Moreover, we showed that greedy miners have a detrimental impact on transaction throughput and have the incentive to form a mining pool, exacerbating the decentralization of the assumed consensus protocols.

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APPENDIX - GLOSSARY

  • A A block in the DAG-PROTOCOL

  • G Greedy strategy, choosing transactions with the highest fees

  • H Honest strategy, choosing random transactions

  • γ Discount function in PHANTOM

  • κ Adversarial mining power

  • λ Block creation time

  • G The number of greedy miners

  • τ Network propagation delay of blocks

  • c Gap parameter in PHANTOM

  • e Euler’s number

  • t Time

  • RTS Random Transaction Selection

  • DAG Directed Acyclic Graph

  • MNE Mixed Nash Equilibrium

  • PNE Pure Nash Equilibrium

  • PoW Proof of Work

  • SPNE Subgame Perfect Nash Equilibrium

Authors:

(1) Martin Peresıni, Brno University of Technology, Faculty of Information Technology (iperesini@fit.vut.cz);

(2) Ivan Homoliak, Brno University of Technology, Faculty of Information Technology (ihomoliak@fit.vut);

(3) Federico Matteo Bencic, University of Zagreb, Faculty of Electrical Engineering and Computing (federico-matteo.bencic@fer.hr);

(4) Martin Hruby, Brno University of Technology, Faculty of Information Technology (hruby@fit.vut.cz);

(5) Kamil Malinka, Brno University of Technology, Faculty of Information Technology (malinka@fit.vut).


This paper is available on arxiv under CC BY 4.0 DEED license.