Authors: Chao Lin, Debiao He, Xinyi Huang, Kim-Kwang Raymond Choo
Title: OBFP: Optimized Blockchain-based Fair Payment for Outsourcing Computations in Cloud Computing
Journal: IEEE Transactions on Information Forensics and Security

Abstract: Outsourcing computations have been an indispensable part to meet the growing demand of computing capability, among which trust problem is one of critical issues to be solved urgently. Fair payment, as a candidate solution, offers the potential for facilitating fair trading among outsourcing computation participants such as users and workers. However, most of existing solutions including traditional e-cash-based or blockchain-based, either require trusted third party or compromise worker's fairness (which does not achieve robust fairness, namely, requiring some trusted third parties during the process of trading), or involve heavy zero-knowledge proofs (ZKPs, which cause huge computation costs). In this paper, we propose a system model of an optimized blockchain-based fair payment (OBFP) for outsourcing computations. Then, we construct a ZKP-free solution based on blockchain by combining any secure commitment, accumulator, and symmetric encryption schemes, as well as hash function. To demonstrate the utility of our proposed OBFP system, we provide a security analysis, performance evaluation and a comparison with existing popular solutions. Specifically, the cryptographic tools are instantiated as commitment (Perdesen commitment), accumulator (RSA-based accumulator), and symmetric encryption (a concrete scheme with the indistinguishability under chosen-plaintext attack (IND-CPA) security), and a hash function (Keccak-256). The prototype is implemented in COSBench and Remix to analyze cloud scalability and concurrency, as well as gas cost.