Encrypted KYC & Anti Money Laundering Data Storage on Chain using Inco and FHE
Context and Importance: KYC (Know Your Customer) and AML (Anti-Money Laundering) processes are crucial in the financial sector to verify the identity of users and prevent fraudulent activities such as money laundering and terrorism financing. In the DeFi space, these processes can enhance security and compliance with regulatory standards, making the ecosystem safer for all participants.
Implementation on-Chain:
Data Collection and Encryption:
- Users provide their identification documents and other necessary information to a trusted KYC provider.
- The KYC provider verifies the data and encrypts it before storing it on-chain. The encryption ensures that only authorized parties with the appropriate decryption keys can access the information.
Storing Encrypted Data:
- The encrypted KYC/AML data is stored on the blockchain, creating an immutable record of the verification status. This data might include a hash of the user's identity documents, proof of address, and other relevant information.
- Smart contracts can be employed to manage access to this data, ensuring that only authorized entities, such as DeFi platforms that comply with KYC/AML regulations, can request access.
Seamless Verification Across Platforms:
- Once the KYC/AML data is on-chain, users do not need to undergo the KYC process multiple times. When they interact with a new DeFi platform, the platform can request access to the already-verified KYC/AML data.
- The user grants permission via a secure method (e.g., using their private key), allowing the DeFi platform to access the encrypted data and verify the user's identity without exposing the raw data.
Privacy Preservation:
- The encryption ensures that even though the data is stored on a public blockchain, it remains confidential. Only the entities with the proper decryption keys can access and interpret the data.
- Techniques like zero-knowledge proofs can further enhance privacy by allowing verification of certain attributes (e.g., age or residency) without revealing the actual data.