FE[r]Chain: Enforcing Fairness in Blockchain Data Exchanges Through Verifiable Functional Encryption

Abstract

Functional Encryption (FE) allows users to extract specific function-related information from encrypted data while preserving the privacy of the underlying plaintext. Though significant research has been devoted to developing secure and efficient Multi-Input Functional Encryption schemes supporting diverse functions, there remains a noticeable research gap in the development of verifiable FE schemes. Functionality and performance have received considerable attention, however, the crucial aspect of verifiability in FE has been relatively understudied. Another important aspect that prior research in FE with outsourced decryption has not adequately addressed is the fairness of the data-for-money exchange between a curator and an analyst. This paper focuses on addressing these gaps by proposing a verifiable FE scheme for inner product computation. The scheme not only supports the multi-client setting but also extends its functionality to accommodate multiple users - an essential feature in modern privacy-respecting services. Additionally, it demonstrates how this FE scheme can be effectively utilized to ensure fairness and atomicity in a payment protocol, further enhancing the trustworthiness of data exchanges.