Asymmetric Fingerprint Scheme for Vector Geographic Data Based on Smart Contracts

Abstract

Existing vector geographic data transaction schemes are typically merchant-controlled, hindering fair ownership tracing and impartial arbitration. To address this, we propose an asymmetric digital fingerprinting scheme based on smart contracts. In our approach, the user encrypts a proof fingerprint with a public key and sends it to the merchant; the merchant leverages the additive homomorphic property of the Paillier cryptosystem to embed the encrypted user fingerprint into an encrypted portion of the vector data while embedding a tracking fingerprint into the plaintext portion. The combined data is delivered to the user, who uses their private key to decrypt the encrypted part and obtain the plaintext data containing both fingerprints. This design enables tracing of unauthorized distribution without exposing the user’s fingerprint in plaintext, preventing malicious accusations. By leveraging blockchain immutability and smart contract automation, the scheme supports secure, transparent transactions and decentralized arbitration without third-party involvement, thereby reducing collusion risk and protecting both parties’ rights.