Agent-based modeling of Sybil attack using network expansion strategies

Abstract Sybil attacks are a significant challenge in permissionless blockchains. However, existing research pays limited attention to how different modes of network evolution affect Sybil resistance. In practice, the method of node admission can greatly influence a blockchain’s resilience to Sybil attacks. To address this, we study Sybil resilience using a dynamic network growth model based on preferential attachment and adopt the Identity-Augmented Proof-of-Stake (IdAPoS) protocol as our consensus backbone. First, we extend IdAPoS with an on-chain Sybil-detection mechanism, reducing reliance on off-chain honesty assumptions. Subsequently, we formalize the network expansion procedure in IdAPoS by distinguishing the Applicant-based and Participant-based Network Expansion Models and assessing Sybil resistance under each model. Finally, using agent-based modeling, we simulate voting token value dynamics under Sybil attacks to quantify how expansion strategies affect Sybil resistance. Experiments show that our proposed trustworthiness-evaluation mechanism removes IdAPoS’s reliance on off-chain honesty information by extracting node-level Sybil-suspicion scores from on-chain voting relationships. Sybil attacks in blockchains cannot be eliminated but can only be delayed. Greater centralization among honest nodes generally strengthens Sybil resistance. Under superlinear network growth, the Participant-based Network Expansion Model achieves more stable scaling than the Applicant-based Network Expansion Model. Overall, IdAPoS improves system-level Sybil resilience at the cost of more centralized voting power.