Trustalabs
{"type": "project", "title": "Trustalabs", "logoImg": "bafkreigcnneexksykfxakpvavb2ysqxrgcwuxhcy3tudqtwui574keof6q", "website": "https://www.trustalabs.ai/", "bannerImg": "bafkreidy6fr4gdqxsxexqma2bqnlpmnq362zetkqjxzmg5tq6le53ggt6q", "createdAt": 1698746671033, "userGithub": "", "credentials": {"twitter": {"type": ["VerifiableCredential"], "proof": {"jws": "eyJhbGciOiJFZERTQSIsImNyaXQiOlsiYjY0Il0sImI2NCI6ZmFsc2V9..fCz5V87Mjbf54rTPAMShsT2-KsS5fsRu-hDuY6-jPWff1GTKkiBK7VnRcCO4NkokIrxDUG-OGkEjEA_mbJSdDQ", "type": "Ed25519Signature2018", "created": "2023-10-31T09:45:00.110Z", "proofPurpose": "assertionMethod", "verificationMethod": "did:key:z6MkghvGHLobLEdj1bgRLhS4LPGJAvbMA1tn2zcRyqmYU5LC#z6MkghvGHLobLEdj1bgRLhS4LPGJAvbMA1tn2zcRyqmYU5LC"}, "issuer": "did:key:z6MkghvGHLobLEdj1bgRLhS4LPGJAvbMA1tn2zcRyqmYU5LC", "@context": ["https://www.w3.org/2018/credentials/v1"], "issuanceDate": "2023-10-31T09:45:00.110Z", "expirationDate": "2024-01-29T09:45:00.110Z", "credentialSubject": {"id": "did:pkh:eip155:1:0xd2C68ad0a5d719E0Ad2C602D5E879B8D9cdbB37B", "hash": "v0.0.0:HaONrl5h9XUU4wfLJNVMISPjpmMuuzwqz524QCJLIFU=", "@context": [{"hash": "https://schema.org/Text", "provider": "https://schema.org/Text"}], "provider": "ClearTextTwitter#TrustaLabs"}}}, "description": "On-chain reputation is revolutionizing the decentralized space – from dApps and DeFi, to DAOs, DeSci, AI, and L2 blockchains. In order to accurately assess users’ contributions to on-chain ecosystems, Trusta Labs has built MEDIA Score based purely on on-chain behaviors at L2. MEDIA Score is an objective, fair and quantifiable metric to comprehensively evaluate accounts’ on-chain engagement and value. By performing in-depth quantification and measurement of user behaviors within the blockchain ecosystem, MEDIA Score assigns a score from 0–100. MEDIA Score’s evaluation system covers not just simple statistics of interaction amounts and values with smart contracts, protocols, and dApps, but more importantly focuses on the breadth and depth of a user’s participation in on-chain activities, their loyalty, and any special identity roles and credentials held by the user.\n\nSybil attacks describe the abuse of a digital network by creating many illegitimate virtual accounts or bots. Sybil attacks will affect the on-chain reputation evaluation on L2 chains. Trusta applied AI and machine learning powered framework to systematically analyze on-chain data and identify suspicious Sybil clusters. The 2-phase approach first uses graph mining algorithms to detect coordinated communities, then refines results with user behavior analysis to reduce false positives. Examples demonstrate how Trusta identified real onchain Sybil clusters on L2 chains. Compared to the Proof-of-personhood methods like biometric scans or social media verification, the AI-ML framework is a robust sybil resistance solution that preserves user privacy and permissionless participation.\n\nTrusta Labs aims to continuously develop MEDIA Score as the infrastructure for on-chain user value assessment. In the KYA (Know Your Account) product called TrustGo (https://trustgo.trustalabs.ai/) from Trusta Labs, every user can look up their own unique MEDIA Score on zkSync/Starknet/Linea/Base. It helps to fairly identify accounts that contribute to the L2 ecosystem. Through MEDIA Score, users can gain a deeper understanding of their on-chain activities and value, while project teams can accurately allocate resources and incentives to users who truly contribute. TrustGo and MEDIA score will accelerate the grow of L2 ecosystem.\n\nMore details:\nhttps://medium.com/@trustalabs.ai/media-score-as-the-infrastructure-for-on-chain-user-value-assessment-c37f68eeb198\n\nhttps://medium.com/@trustalabs.ai/trustas-ai-and-machine-learning-framework-for-robust-sybil-resistance-in-airdrops-ba17059ec5b7", "logoImgData": {}, "bannerImgData": {}, "projectTwitter": "trustalabs"}