Charge Your Clients: Payable Secure Computation and Its Applications

Abstract

The online realm has witnessed a surge in the buying and selling of data, prompting the emergence of dedicated data marketplaces. These platforms cater to servers (sellers), enabling them to set prices for access to their data, and clients (buyers), who can subsequently purchase these data, thereby streamlining and facilitating such transactions. However, the current data market is primarily confronted with the following issues. Firstly, they fail to protect client privacy, presupposing that clients submit their queries in plaintext. Secondly, these models are susceptible to being impacted by malicious client behavior, for example, enabling clients to potentially engage in arbitrage activities. To address the aforementioned issues, we propose payable secure computation, a novel secure computation paradigm specifically designed for data pricing scenarios. It grants the server the ability to securely procure essential pricing information while protecting the privacy of client queries. Additionally, it fortifies the server’s privacy against potential malicious client activities. As specific applications, we have devised customized payable protocols for two distinct secure computation scenarios: Keyword Private Information Retrieval (KPIR) and Private Set Intersection (PSI). We implement our two payable protocols and compare them with the state-of-the-art related protocols that do not support pricing as a baseline. Since our payable protocols are more powerful in the data pricing setting, the experiment results show that they do not introduce much overhead over the baseline protocols. Our payable KPIR achieves the same online cost as baseline, while the setup is about $1.3-1.6\times $ slower than it. Our payable PSI needs about $2\times $ more communication cost than that of baseline protocol, while the runtime is $1.5-3.2\times $ slower than it depending on the network setting.