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.

翻译：平台发行的空投旨在分发代币、推动用户采用并促进去中心化服务。这些分发活动吸引了空投猎人（攻击者），他们通过实施女巫攻击（即使用多重身份操纵代币分配以满足资格标准）来利用系统。尽管围绕空投狩猎的争论质疑其对生态系统的潜在益处，但女巫攻击等剥削行为显然破坏了系统的完整性，侵蚀了信任与可信度。尽管这些策略日益普遍，但现有文献在空投猎人成本与收益的系统化建模，以及捕捉空投机制设计中所有角色间相互作用的理论模型方面仍存在空白。本研究首先对Hop Protocol和LayerZero的交易数据进行实证分析，识别普遍的攻击模式并估算猎人的预期收益。此外，我们构建了一个博弈论模型，模拟攻击者、组织者和赏金猎人之间的互动，提出能增强检测能力同时最小化组织成本的最优激励结构。