High-Speed Private Information Retrieval Computation on GPU

40 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

XPIR : Private Information Retrieval for Everyone (2016, background): “The (broken) schemes of Aguilar et al. [7] and Tros-tle and Parrish [8] represented the state-of-the-art in ef-ﬁcient private information retrieval, allowing to reach processing speeds of hundreds of megabits per second on high-end CPUs and up to one gigabit per second on GPUs [14].”
The Best of Both Worlds: Combining Information-Theoretic and Computational PIR for Communication Efficiency (2014, background): “paper [1] and by Olumofin and Goldberg [23], the protocol resists known lattice-based attacks, but the protocol and its privacy assumptions are new and may not be secure.”
Scalable and Private Media Consumption with Popcorn (2016, background): “ous CPIR implementations [11, 30, 41, 70, 72, 80, 87, 97, 99, 103], among which XPIR [11] is the fastest.”
Bandwidth Efficient PIR from NTRU (2014, methodology): “Using the complexities compared to other schemes, our query size is smaller by a factor of 1024, 1200, and 3072 compared to BGN, Melchor-Gaborit and Kushilevitz-Ostrovsky respectively.”