Towards Doubly Efficient Private Information Retrieval
By Ran Canetti, Justin Holmgren, Silas Richelson. 2017
77 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computational Theory and Mathematics
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Sarvar Patel
- Kevin Yeo
- Srinath T. V. Setty
- Mariana Raykova
- Karn Seth
- Phillipp Schoppmann
- Tancrède Lepoint
- Kim Laine
In Computational Theory and Mathematics
- Sarvar Patel
- Mariana Raykova
- Kevin Yeo
- Srinath T. V. Setty
- Karn Seth
- Tancrède Lepoint
- Kim Laine
- Hao Chen
Citations in the corpus
- Private Stateful Information Retrieval (2018, methodology): “[15] present symmetric-key DEPIR schemes in the single-server setting using locally decodable codes built from Reed-Muller codes [42, 46].”
- PIR with Compressed Queries and Amortized Query Processing (2018, methodology): “This works well, so recent works [15, 21] employ an analogous preprocessing approach in CPIR schemes.”
- Communication-Computation Trade-offs in PIR (2019, background): “Two works [10, 12] consider doubly-efficient PIRs that attempt to obtain schemes with sub-linear computational costs, but require both significant server overhead and new cryptographic assumptions precluding them from practical applications.”