Toward Resilient Airdrop Mechanisms: Empirical Measurement of Hunter Profits and Airdrop Game Theory Modeling
Luo, Junliang Kang, Hong Zheng, Shuhao Liu, Xue
Luo, Junliang
Kang, Hong
Zheng, Shuhao
Liu, Xue
Supervisor
Department
Machine Learning
Embargo End Date
Type
Conference proceeding
Date
2025
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Language
English
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Research Projects
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Abstract
Airdrops issued by platforms are to distribute tokens, drive user adoption, and promote decentralized services. The distributions attract airdrop hunters (attackers), who exploit the system by employing Sybil attacks, i.e., using multiple identities to manipulate token allocations to meet eligibility criteria. While debates around airdrop hunting question the potential benefits to the ecosystem, exploitative behaviors like Sybil attacks clearly undermine the system’s integrity, eroding trust and credibility. Despite the increasing prevalence of these tactics, a gap persists in the literature regarding systematic modeling of airdrop hunters’ costs and returns, alongside the theoretical models capturing the interactions among all roles for airdrop mechanism design. Our study first conducts an empirical analysis of transaction data from the Hop Protocol and LayerZero, identifying prevalent attack patterns and estimating hunters’ expected profits. Furthermore, we develop a game-theory model that simulates the interactions between attackers, organizers, and bounty hunters, proposing optimal incentive structures that enhance detection while minimizing organizational costs.
Citation
J. Luo, H. Kang, S. Zheng and X. Liu, "Toward Resilient Airdrop Mechanisms: Empirical Measurement of Hunter Profits and Airdrop Game Theory Modeling," 2025 IEEE International Conference on Blockchain and Cryptocurrency (ICBC), Pisa, Italy, 2025, pp. 1-5, doi: 10.1109/ICBC64466.2025.11114597.
Source
Proceedings of IEEE International Conference on Blockchain and Cryptocurrency (ICBC)
Conference
2025 IEEE International Conference on Blockchain and Cryptocurrency (ICBC)
Keywords
Airdrop Hunters, Empirical Hunter Patterns, Expected Profit Measurement, Game Theory Model
Subjects
Source
2025 IEEE International Conference on Blockchain and Cryptocurrency (ICBC)
Publisher
IEEE