Outsourced Privacy-Preserving Data Alignment on Vertically Partitioned Database

In the context of real-world secure outsourced computations, private data alignment has been always the essential preprocessing step. However, current private data alignment schemes, mainly circuit-based, suffer from high communication overhead and often need to transfer potentially gigabytes of data. In this paper, we propose a lightweight private data alignment protocol (called SC-PSI) that can overcome the bottleneck of communication. Specifically, SC-PSI involves four phases of computations, including data preprocessing, data outsourcing, private set member (PSM) evaluation and circuit computation (CC). Like prior works, the major overhead of SC-PSI mainly lies in the latter two phases. The improvement is SC-PSI utilizes the function secret sharing technique to develop the PSM protocol, which avoids the multiple rounds of communication to compute intersection set members. Moreover, benefited from our specially designed PSM protocol, SC-PSI does not to execute complex secure comparison circuits in the CC phase. Experimentally, we validate that compared to prior works, SC-PSI can save around 61.39% running time and 89.61% communication overhead.

Automated summary

In the context of real-world secure outsourced computations, private data alignment, mainly circuit-based, suffers from high communication overhead and often needs to transfer gigabytes of data. In this paper, a lightweight private data alignment protocol (SC-PSI) is proposed to overcome the bottleneck of communication. SC-PSI utilizes the function secret sharing technique to develop the PSM protocol, which avoids multiple rounds of communication and complex secure comparison circuits.