Towards Doubly Efficient Private Information Retrieval

被引:37
|
作者
Canetti, Ran [1 ,2 ]
Holmgren, Justin [3 ]
Richelson, Silas [4 ]
机构
[1] Boston Univ, Boston, MA 02215 USA
[2] Tel Aviv Univ, Tel Aviv, Israel
[3] MIT, Cambridge, MA 02139 USA
[4] Univ Calif Riverside, Riverside, CA 92521 USA
来源
关键词
D O I
10.1007/978-3-319-70503-3_23
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 obtain data from a public database without disclosing the locations accessed. Traditionally, the stress is on preserving sublinear work for the client, while the server's work is taken to inevitably be at least linear in the database size. Beimel, Ishai and Malkin (JoC 2004) show PIR schemes where, following a linear-work preprocessing stage, the server's work per query is sublinear in the database size. However, that work only addresses the case of multiple non-colluding servers; the existence of single-server PIR with sublinear server work remained unaddressed. We consider single-server PIR schemes where, following a preprocessing stage in which the server obtains an encoded version of the database and the client obtains a short key, the per-query work of both server and client is polylogarithmic in the database size. Concentrating on the case where the client's key is secret, we show: - A scheme, based on one-way functions, that works for a bounded number of queries, and where the server storage is linear in the number of queries plus the database size. - A family of schemes for an unbounded number of queries, whose security follows from a corresponding family of new hardness assumption that are related to the hardness of solving a system of noisy linear equations. We also show the insufficiency of a natural approach for obtaining doubly efficient PIR in the setting where the preprocessing is public.
引用
收藏
页码:694 / 726
页数:33
相关论文
共 50 条
  • [31] Heterogeneous Private Information Retrieval
    Mozaffari, Hamid
    Houmansadr, Amir
    27TH ANNUAL NETWORK AND DISTRIBUTED SYSTEM SECURITY SYMPOSIUM (NDSS 2020), 2020,
  • [32] Semantic Private Information Retrieval
    Vithana, Sajani
    Banawan, Karim
    Ulukus, Sennur
    IEEE TRANSACTIONS ON INFORMATION THEORY, 2022, 68 (04) : 2635 - 2652
  • [33] TOWARDS INFORMATION RETRIEVAL
    LINN, M
    AMERICAN DOCUMENTATION, 1966, 17 (02): : 109 - &
  • [34] On the Information Leakage in Private Information Retrieval Systems
    Guo, Tao
    Zhou, Ruida
    Tian, Chao
    2020 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY (ISIT), 2020, : 1018 - 1023
  • [35] On the Information Leakage in Private Information Retrieval Systems
    Guo, Tao
    Zhou, Ruida
    Tian, Chao
    IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, 2020, 15 (15) : 2999 - 3012
  • [36] XSPIR: Efficient Symmetrically Private Information Retrieval from Ring-LWE
    Lin, Chengyu
    Liu, Zeyu
    Malkin, Tal
    COMPUTER SECURITY - ESORICS 2022, PT I, 2022, 13554 : 217 - 236
  • [37] Byzantine-Robust Private Information Retrieval with Low Communication and Efficient Decoding
    Zhang, Liang Feng
    Wang, Huaxiong
    Wang, Li-Ping
    ASIA CCS'22: PROCEEDINGS OF THE 2022 ACM ASIA CONFERENCE ON COMPUTER AND COMMUNICATIONS SECURITY, 2022, : 1079 - 1085
  • [38] Noisy Private Information Retrieval: On Separability of Channel Coding and Information Retrieval
    Banawan, Karim
    Ulukus, Sennur
    IEEE TRANSACTIONS ON INFORMATION THEORY, 2019, 65 (12) : 8232 - 8249
  • [39] On Single Server Private Information Retrieval With Private Coded Side Information
    Lu, Yuxiang
    Jafar, Syed A.
    IEEE TRANSACTIONS ON INFORMATION THEORY, 2023, 69 (05) : 3263 - 3284
  • [40] Private Information Retrieval with Private Side Information Under Storage Constraints
    Wei, Yi-Peng
    Ulukus, Sennur
    2018 IEEE INFORMATION THEORY WORKSHOP (ITW), 2018, : 345 - 349