Two-Server Private Information Retrieval with High Throughput and Logarithmic Bandwidth
Bibliographic record
Abstract
In this paper, we propose a high-throughput, logarithmic-bandwidth private information retrieval (PIR) scheme, which enables a client to securely retrieve any record from a database replicated on two remote servers without revealing the record index. Specifically, based on the puncturable pseudorandom function (PPRF), a client first leverages randomized mapping to locate a logarithmic-size punctured PRF key capable of replacing a randomized set of arbitrary size while concealing a chosen element within the set. With the key, the client then generates corresponding PIR queries for two servers, achieving logarithmic communication complexity. Upon receiving the queries, the servers independently perform level-I PPRF evaluations on partitioned databases, i.e., buckets, to obtain intermediate results, and cooperatively perform level-II PPRF evaluations on these results to provide fast PIR responses. The two-level recursive approach can significantly reduce the servers’ computational complexity from linear to sublinear, ensuring high throughput. Finally, we conduct a comprehensive security analysis and develop a proof-of-concept prototype to demonstrate the efficiency and security of the proposed PIR scheme.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".