OBFP: Optimized Blockchain-Based Fair Payment for Outsourcing Computations in Cloud Computing

Outsourcing computations have been widely used to meet the growing computing demands, although achieving trust in an untrusted (or a zero-trust) environment can be challenging in practice. Fair payment, a candidate solution, can potentially facilitate fair trading among outsourcing computation participants such as users and workers. However, most existing solutions including traditional e-cash-based or blockchain-based, may potentially compromise the worker's fairness (i.e., does not achieve robust fairness, since trusted third parties are required during the trading process), or involve heavy zero-knowledge proofs (ZKPs, with significant computation costs). To mitigate these limitations, 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 a hash function. To demonstrate the utility of our proposed OBFP system, we provide 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.

Automated summary

This research explores the challenge and solution of fair payment in outsourcing computations, proposing an optimized blockchain-based fair payment system model and constructing a blockchain-based solution that does not require zero-knowledge proofs. The utility of the system is demonstrated through security analysis, performance evaluation, and comparison with existing solutions.