Revisiting Hybrid Private Information Retrieval

被引:1
|
作者
Guenther, Daniel [1 ]
Schneider, Thomas [1 ]
Wiegand, Felix [1 ]
机构
[1] Tech Univ Darmstadt, Darmstadt, Germany
基金
欧洲研究理事会;
关键词
Private Information Retrieval; Large-Scale Applications;
D O I
10.1145/3460120.3485346
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Private Information Retrieval (PIR) allows a client to request entries from a public database held by k servers without revealing any information about the requested data to the servers. PIR is classified into two classes: (i) Multi-server PIR protocols where the request is split among k >= 2 non-colluding servers, and (ii) Single-server PIR protocols where exactly k = 1 server holds the database while the query is protected via certain computational hardness assumptions. Devet & Goldberg (PETS '14) showed that both can be combined into one recursive PIR protocol in order to improve the communication complexity. Their hybrid PIR protocol is instantiated with the multi-server PIR protocol of Goldberg (S&P'07) and the single-server PIR protocol by Melchar & Gaborit (WEWoRC'07), resulting in online request runtime speedups and guaranteeing at least partial privacy if the multi-server PIR servers do in fact collude. In this work we show that the hybrid PIR protocol by Devet & Goldberg still has practical relevance by designing a hybrid approach using the state-of-the-art multi-server protocol CIP-PIR (Gunther et al., ePrint '21/823) and the single-server protocol SealPIR (Angel et al., S&P '18). Our novel hybrid PIR protocol massively improves the linear communication complexity of CIP-PIR and obtains the strong property of client-independent preprocessing, which allow batch-preprocessing among multiple clients without the clients being involved. We implement and benchmark our protocol and get speedups of approximate to 4.36x over the original implementation of Devet & Goldberg (8 GiB DB), speedups of approximate to 26.08x (8 GiB DB) over CIP-PIR, and speedups of approximate to 11.16x over SealPIR (1 GiB DB).
引用
收藏
页码:2408 / 2410
页数:3
相关论文
共 50 条
  • [31] Vectorized Batch Private Information Retrieval
    Mughees, Muhammad Haris
    Ren, Ling
    2023 IEEE SYMPOSIUM ON SECURITY AND PRIVACY, SP, 2023, : 437 - 452
  • [32] Asymmetric Leaky Private Information Retrieval
    Samy, Islam
    Attia, Mohamed
    Tandon, Ravi
    Lazos, Loukas
    IEEE TRANSACTIONS ON INFORMATION THEORY, 2021, 67 (08) : 5352 - 5369
  • [33] Weakly-Private Information Retrieval
    Lin, Hsuan-Yin
    Kumar, Siddhartha
    Rosnes, Eirik
    Graell i Amat, Alexandre
    Yaakobi, Eitan
    2019 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY (ISIT), 2019, : 1257 - 1261
  • [34] On the Storage Cost of Private Information Retrieval
    Tian, Chao
    IEEE TRANSACTIONS ON INFORMATION THEORY, 2020, 66 (12) : 7539 - 7549
  • [35] On the Capacity of Leaky Private Information Retrieval
    Samy, Islam
    Tandon, Ravi
    Lazos, Loukas
    2019 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY (ISIT), 2019, : 1262 - 1266
  • [36] Degree Tables for Private Information Retrieval
    Kazemi, Fatemeh
    Wang, Ningze
    D'Oliveira, Rafael G. L.
    Sprintson, Alex
    2022 58TH ANNUAL ALLERTON CONFERENCE ON COMMUNICATION, CONTROL, AND COMPUTING (ALLERTON), 2022,
  • [37] The Capacity of Private Information Retrieval with Eavesdroppers
    Wang, Qiwen
    Sun, Hua
    Skoglund, Mikael
    2018 CONFERENCE RECORD OF 52ND ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS, AND COMPUTERS, 2018, : 1679 - 1683
  • [38] A Stochastic Approach in Private Information Retrieval
    Seo, Hyowoon
    Choi, Wan
    2018 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE (WCNC), 2018,
  • [39] Improving the robustness of private information retrieval
    Goldberg, Ian
    2007 IEEE SYMPOSIUM ON SECURITY AND PRIVACY, PROCEEDINGS, 2007, : 131 - 145
  • [40] Batched Differentially Private Information Retrieval
    Albab, Kinan Dak
    Issa, Rawane
    Varia, Mayank
    Graffi, Kalman
    PROCEEDINGS OF THE 31ST USENIX SECURITY SYMPOSIUM, 2022, : 3327 - 3344