Sybil attacks are the hiddren threats behind bots, airdrops, and daos. This is one huge problem @Humanityprot is here to solve, by helping build the TRUST LAYER for not just web3, but the the internet in general, especially its participants. A sybil attack happens when one person creates many fake identities to manipulate a decentralized system. Some of the problems sybil attacks can cause are... 1. They distort incentives distribution 2. Abuse of airdrop intent by these protocols. 3. The governance of a protocol is affected as some persons can own multiple tokens using different wallets and hence vote multiple times during key decision-making periods. 4. Makes web3 dapps/protocols less fair and less functional. 5. Fakeness in growth data and increased wrong metrics (botted), inflated adoption stats, thereby misleading teams and investors. Currently, even in @Humanityprot , we have 8m IDS generated, which isn't proven true as not all have been verified with the palm scan biometrics feature. To curb these issues/problems, SYBIL RESISTANCE must be put in place so that each participant is a unique individual and not a fake identity created to exploit the network. Some previous sybil detection methods adopted in web3 👇 1. Double checking with previous sybil clusters. 2. Checking onchain data 3. Ranking of social tasks (Leaderboards, etc, moderately relevant). 4. Linking social handles like telegram and discords. Well, welcome to the hive as many people create alt accounts, which becomes undetectable. 5. Token/NFT-Gating ( buy and own more tokens across different wallets, mint more NFTs. 6. KYC - The closest so far to perfection. However, most users prefer their privacy and data. 7. Minting wallet ID (More can be minted, simply create more wallets 😅). 8. Captcha - Easily bypassed as bots solve them easily or outsource them for a few pennies. However, with upgrades in technology and newer integrations to the blockchain, new features like 👇 1. User of web3-native identiry proofs (use of Zk proofs and biometrics) 2. Making fake accounts costly to scale/create. How? By using staking or computing costs (like in POS/POW). 3. Leveraging machine learning detection to flag sybil behavior through onchain activity platform. 4. Social Graph Analysis ( @KaitoAI adopts this), i.e., detecting identity clusters using connection mapping. The team @Humanityprot understands that sybil resistance isn't optional in web3 if they are to thrive on the foundation of trust, fairness, and growth. @Humanityprot has adopted the Proof of Humanity Consensus and integrated Identity validators (Nodes that can verify identity and add them onchain, thus playing a crucial role in ensuring the security, accuracy, and integrity of the blockchain by preventing identity fraud and enforcing the network's rules). This is also enabled by the use of Zero Knowledge Proofs for Trust and authenticity of human IDs, ensuring their privacy. With Zk Proofs, POH, and Palm scan, identity becomes verifiable, unique, and self-owned. With the upcoming humanity protocol gamechanger called FAIRDROP and a pipeline of projects planning to launch their airdrops through fairdrops, @Humanityprot will eliminate such incentive distribution issues, ensure fairness and reward genuine users. I'm super bullish on Humanity Protocol, you definitely need to do the same. gHuman to @TK_Humanity, his team and to every believer out there. #HumanityProtocol