A Novel Graph Based Algorithm to Counter Sybil Attacks in Reputation Systems Built on Blockchain

The proliferation of Sybil attacks in Peer-to-Peer (P2P) blockchain networks poses a significant threat to trust, transparency, and security. A Sybil attack involves an adversary assuming multiple fake identities, manipulating the network, and wielding undue influence over decentralized decision-making processes. This paper explores the development of a Sybil attack-resistant reputation system tailored for P2P blockchain networks. This work also conducts a comprehensive literature review, focusing on the Decentralized Reputation Trilemma, which underscores the difficulty of creating a reputation system that is simultaneously generalizable, trustless, and Sybil-resistant. Traditional solutions like Trusted Oracles, Cryptographic Proofs, and Feedback Aggregation are analyzed, each with its limitations and trade-offs. Notably, Feedback Aggregation offers a promising direction. Experimental results demonstrate that the proposed asymmetric version of our algorithm remains highly effective even when 80–90% of the network consists of Sybil nodes, significantly outperforming existing Sybil-tolerant reputation mechanisms. Ultimately, this research strives to contribute to developing a resilient reputation system that balances trustlessness, generalizability, and Sybil resistance, thereby fortifying the foundations of trust and security in decentralized blockchain ecosystems.