"Performance Dataset: Efficient Cloud-Assisted Laconic PSI-CA (Linear Communication Complexity)"

"Private set intersection cardinality (PSI-CA) enables multiple parties to jointly compute the size of the intersection of their private datasets without revealing any additional information. Existing cloud-assisted laconic PSI-CA protocols, which rely on two non-colluding cloud servers, eliminate direct communication between parties and require at most two rounds of interaction per party. However, they still incur non-linear computation and communication overheads, which hinder their practical deployment.To address the performance limitations, we propose single-server-assisted laconic PSI-CA protocols based on oblivious key-value stores (OKVS) and bilinear pairings under the semi-honest model, supporting both two-party and multi-party settings.We compare the experimental performance of our protocol with state-of-the-art cloud-assisted laconic PSI-CA protocols, showing that our receiver in the two-party setting and leader in the multi-party setting achieve $23.2\\sim48.7\\times$ and $2498.4\\sim4022.4\\times$ lower computation, respectively, and $58.0\\sim232.1\\times$ and $7418.1\\sim29672.4\\times$ lower communication overhead. Meanwhile, the monetary cost of the cloud server is reduced by $11.4\\sim44.7\\times$ and $2999.2\\sim4705.6\\times$, respectively."