发表机构
Exponential Science Foundation; King’s College London（指数科学基金会; 伦敦国王学院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
研究NFT奖励机制中Sybil农场攻击的威慑问题，提出随机验证与归属期结合的最优策略，并区分惩罚与簇级审计的作用，为高吞吐量账本设计提供指导。
AI 中文摘要
我们研究了基于NFT的奖励机制，在该机制中，用户可创建多个身份并提交欺诈性索赔，这些索赔在满足归属期条件后成熟并获得奖励。我们假设发行方在归属期内对索赔进行随机验证，且身份可被关联成簇，使得检测到某个身份提交欺诈性索赔时，整个簇将通过惩罚被没收。因此，农场攻击者的收益在身份数量上呈非线性：奖励线性增加，而避免被检测的概率则呈几何级数下降。我们在问题的连续松弛形式下刻画了最优的农场攻击规模。这使我们能够推导出威慑的充分条件，进而考虑发行方对奖励归属期和索赔验证的选择。归属期降低了欺诈性索赔获得支付的概率，但也影响了真实参与者，而验证对发行方而言是有成本的。我们根据审计成本、归属期安排和惩罚值，刻画了发行方的充分威慑边界。当可以以可忽略的边际成本增加少量审计能力时，仅靠归属期并非最优。我们还区分了惩罚与簇级审计的不同作用。最后，我们讨论了这些发现对高吞吐量账本（如Hedera）上NFT奖励计划的影响。
英文摘要
We study NFT-based reward mechanisms in which a user can create multiple identities and submit fraudulent claims that mature a reward subject to vesting. We assume that the issuer stochastically verifies claims during the vesting period and that identities can be linked into clusters so that the detection of one identity submitting a fraudulent claim causes the whole cluster to be forfeited through a penalty. A farmer's payoff is then non-linear in the number of identities: rewards increase linearly, while the probability of avoiding detection decreases geometrically. We characterise the optimal farming scale in the continuous relaxation of the problem. This allows us to derive a sufficient condition for deterrence and then consider the issuer's choice of reward vesting and claim verification. Vesting reduces the probability that a fraudulent claim is paid but also affects genuine participants, while verification is costly for the issuer. We characterise the sufficient deterrence frontier for the issuer in terms of auditing cost, vesting schedule, and penalty value. When small amounts of audit capacity can be added at negligible marginal cost, vesting alone is not optimal. We also distinguish the role of penalties from that of cluster-level auditing. Finally, we discuss the implications for NFT reward programmes on high-throughput ledgers, such as Hedera.
