RAID-PIR: Practical Multi-Server PIR

By Daniel Demmler, Amir Herzberg, Thomas Schneider. 2014

68 citations recorded by the source corpus.

Private Information Retrieval (PIR) allows to privately request a block of data from a database such that no information about the queried block is revealed to the database owner. With the rapid rise of cloud computing, data is often shared across multiple servers, making multi-server PIR a promising privacy-enhancing technology. In this paper, we introduce RAID-PIR, an efficient and simple multi-server PIR scheme, which has similar approach to RAID (Redundant Arrays of Inexpensive Disks) systems. Each server stores only a part of the database, its computational complexity depends only on this part, and multiple blocks can be queried efficiently in parallel. RAID-PIR improves efficiency over known PIR protocols, using only very efficient cryptographic primitives (pseudo-random generator). We demonstrate that RAID-PIR is practical and well-suited for cloud deployment as it reduces the communication as well as the computational workload per server.

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Citations in the corpus

PIR with Compressed Queries and Amortized Query Processing (2018, background): “1 In IT-PIR schemes [11, 28, 31, 32, 41] the database is replicated across several non-colluding servers.”
Scalable and Private Media Consumption with Popcorn (2016, methodology): “Another recent system, RAID-PIR [32], based on the implementation of upPIR [24], reduces the server-side work, first, by storing and processing only a fraction of the library at each ITPIR server and, second, by encoding multiple requests from the same client in a single query.”
Optimal Rate Private Information Retrieval from Homomorphic Encryption (2015, background): “See [14, 15, 31] and references therein for other possible optimizations.”
Polynomial Batch Codes for Efficient IT-PIR (2016, methodology): “Although this model has been used implicitly in several recent papers [21, 34, 39, 51], a rigorous security definition is lacking from the literature; for completeness, we therefore provide such a definition.”
Communication-Computation Trade-offs in PIR (2019, background): “Non-trivial single server PIR constructions are known to require computational assumptions [45], and such solutions bring significant overheads for both the communication and computation costs compared to information theoretic constructions that are possible in the multi-server setting [23].”