Yearn.finance price

Can .@rainbowdotme, @miranetwork, and @GOATRollup build a cross-chain identity system for the AI agent economy? Rainbow's ENS-based identity layer operates as a human-readable interface for users and agents, while Mira cryptographically proves the actions or facts of AI agents, and Goat enables the use of these identity credentials within a Bitcoin-based payment network. By combining these three layers, AI agents can hold portable credentials that can exchange reputations between AI finance (AIFi) and Bitcoin finance (BTCFi) and perform decentralized KYC procedures with optional disclosure features. This structure mitigates key risks through zero-knowledge proofs, token slashing, and workload identity systems. Rainbow connects the user's 'user.eth' with the credential hash using ENS text records. Mira signs verifiable credentials (VC) in JSON-LD format based on results derived from consensus among multiple models, while Goat fixes the hash on the Bitcoin blockchain using BitVM2 and ZK rollups. This allows anyone to verify Mira's validation signature by interpreting the DID and public key through ENS on any blockchain. Users issue their 'agent.eth' address and link it to the credential hash issued by Mira, then send the same hash as a L2 transaction to Goat. As a result, EVM or Bitcoin-based dApps can verify credentials through ENS to perform reliable identity verification. This system ensures chain independence based on public standards such as W3C DID, VC, ERC-721, ERC-8004, and JSON-LD. This allows Mira to convert reputation information based on BTCFi transaction history or profit and loss data into verifiable credentials for reuse in AI finance platforms. Conversely, credentials verified by Mira as 'transaction signal providers' or 'verified algorithm traders' can be used as criteria for granting leverage limits on Goat's DEX platform. This process does not involve moving tokens directly, thus avoiding traditional bridge security risks. In the decentralized KYC process, users perform zero-knowledge proof-based KYC through zkPass or Billions Network, and Mira verifies this to update the 'still regulatory compliant' status. The Rainbow wallet presents a ZKP proving that the ENS text record and VC hash match, while Goat's smart contract verifies this without exposing personal information. This method satisfies both anti-money laundering regulations and privacy protection. As a response to security risks, first, there is a method to reissue short-lived keys through Mira to prevent the theft of agents' private keys and periodically replace ENS records. Second, a distributed sharding structure and staking slashing mechanism are used in conjunction to prevent malicious Mira validators from reconstructing data during the verification process. Third, if a forged VC hash is submitted on the Goat network, discrepancies are proven through BitVM2's optimistic challenge structure, and the sequencer is penalized. Fourth, to prevent forged KYC issues through AI-generated faces, biometric verification items are included in the VC, and periodic re-verification is performed. The technical implementation procedure involves converting the VC signed by Mira into a base64 hash and storing it in the ENS text field, with RainbowKit middleware exposing it to the dApp. Goat's L2 verifier checks the match between the signature and the ENS owner's reference to Mira's public root. Users submit credentials in the form of zero-knowledge proofs containing only the necessary items, and when Mira issues a revocation event, Rainbow deactivates the badge, and Goat rejects the related transaction. In conclusion, the combination of Rainbow, Mira, and Goat builds a cross-chain identity system that ensures both privacy and reliability. AI agents can operate across different financial ecosystems with portable credentials, and reputations move without asset transfers. Additionally, automated KYC and verification procedures maintain both regulatory compliance and decentralization. The remaining task is merely the implementation of middleware such as the ENS resolver and Goat's VC verification module, and the overall risk remains at a sufficiently controllable level through zero-knowledge proofs and economic slashing.

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