Efficient Private File Retrieval by Combining ORAM and PIR
By Travis Mayberry, Erik-Oliver Blass, Agnes Hui Chan. 2014
97 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition
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
- Srinath T. V. Setty
- Elaine Shi
- Michael Walfish
- Xiao Shaun Wang
- T-H. Hubert Chan
- Daji Qiao
- Jinsheng Zhang
- Wensheng Zhang
In Computer Vision and Pattern Recognition
- Laurent Fousse
- Marc-Olivier Killijian
- Joris Barrier
- Carlos Aguilar Melchor
- Elaine Shi
- Michael Walfish
- Srinath T. V. Setty
- Xiao Shaun Wang
Citations in the corpus
- XPIR : Private Information Retrieval for Everyone (2016, background): “These works total about eighty citations, and have been used as a fundamental building block (or as a benchmark) in major and recent venues such as Usenix Security [15] (2011), NDSS [16, 17] (2013, 2014), and PETs [18, 19, 20, 21] (2010, 2012,”
- Scalable and Private Media Consumption with Popcorn (2016, background): “Oblivious RAM (ORAM) [49, 69, 71, 94] algorithms allow a client to conceal its access patterns from a storage server.”
- Circuit ORAM: On Tightness of the Goldreich-Ostrovsky Lower Bound (2015, background): “These schemes are conceptually simpler, statistically secure, and easy to implement in secure processors [12, 14, 37, 47] or MPC applications [16,25,28,33,53].”
- MU-ORAM: Dealing with Stealthy Privacy Attacks in Multi-User Data Outsourcing Services (2016, background): “Derived from these constructions, numerous variants [3–6, 9, 10, 12, 24, 26–28, 30–32, 35, 38, 39, 44] have been proposed to further improve the performance, especially the communication performance.”