EncKV: An Encrypted Key-value Store with Rich Queries

被引:36
|
作者
Yuan, Xingliang [1 ,2 ]
Guo, Yu [1 ]
Wang, Xinyu [1 ,2 ]
Wang, Cong [1 ,2 ]
Li, Baochun [3 ]
Jia, Xiaohua [1 ]
机构
[1] City Univ Hong Kong, Dept Comp Sci, Hong Kong, Peoples R China
[2] City Univ Hong Kong, Shenzhen Res Inst, Hong Kong, Peoples R China
[3] Univ Toronto, Dept Elect & Comp Engn, Toronto, ON, Canada
关键词
Encrypted Key-value Store; Searchable Encryption; Order-revealing Encryption;
D O I
10.1145/3052973.3052977
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Distributed data stores have been rapidly evolving to serve the needs of large-scale applications such as online gaming and real-time targeting. In particular, distributed key-value stores have been widely adopted due to their superior performance. However, these systems do not guarantee to provide strong protection of data confidentiality, and as a result fall short of addressing serious privacy concerns raised from massive data breaches. In this paper, we introduce EncKV, an encrypted key-value store with secure rich query support. First, EncKV stores encrypted data records with multiple secondary attributes in the form of encrypted key-value pairs. Second, it leverages the latest practical primitives for searching over encrypted data, i.e., searchable symmetric encryption and order-revealing encryption, and provides encrypted indexes with guaranteed security to support exact-match and range-match queries via secondary attributes of data records. Third, it carefully integrates these indexes into a distributed index framework to facilitate secure query processing in parallel. To mitigate recent inference attacks on encrypted database systems, EncKV protects the order information during range queries, and presents an interactive batch query mechanism to further hide the associations across data values on different attributes. We implement an EncKV prototype on a Redis cluster, and conduct an extensive set of performance evaluations on the Amazon EC2 public cloud platform. Our results show that EncKV effectively preserves the efficiency and scalability of plaintext distributed key-value stores.
引用
下载
收藏
页码:423 / 435
页数:13
相关论文
共 50 条
  • [41] A Multicore-Friendly Persistent Memory Key-Value Store
    Wang Q.
    Zhu B.
    Shu J.
    Jisuanji Yanjiu yu Fazhan/Computer Research and Development, 2021, 58 (02): : 397 - 405
  • [42] FASTER: An Embedded Concurrent Key-Value Store for State Management
    Chandramouli, Badrish
    Prasaad, Guna
    Kossmann, Donald
    Levandoski, Justin
    Hunter, James
    Barnett, Mike
    PROCEEDINGS OF THE VLDB ENDOWMENT, 2018, 11 (12): : 1930 - 1933
  • [43] SKV: A SmartNIC-Offloaded Distributed Key-Value Store
    Sun, Shangyi
    Zhang, Rui
    Yan, Ming
    Wu, Jie
    2022 IEEE INTERNATIONAL CONFERENCE ON CLUSTER COMPUTING (CLUSTER 2022), 2022, : 1 - 11
  • [44] Generalization and Implementation of RAM-Based Key-Value Store
    Tian, Tian
    Zhang, Chengfei
    Yu, Kai
    Zhang, Yiming
    Zhong, Ping
    2016 INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE & COMPUTATIONAL INTELLIGENCE (CSCI), 2016, : 1412 - 1413
  • [45] TurboHash: A Hash Table for Key-value Store on Persistent Memory
    Zhao, Xingsheng
    Zhong, Chen
    Jiang, Song
    PROCEEDINGS OF THE 16TH ACM INTERNATIONAL SYSTEMS AND STORAGE CONFERENCE, SYSTOR 2023, 2023, : 35 - 48
  • [46] KVLight: A Lightweight Key-Value Store for Distributed Access in Cloud
    Zeng, Jiaan
    Plale, Beth
    2016 16TH IEEE/ACM INTERNATIONAL SYMPOSIUM ON CLUSTER, CLOUD AND GRID COMPUTING (CCGRID), 2016, : 473 - 482
  • [47] Building an Efficient Key-Value Store in a Flexible Address Space
    Chen, Chen
    Zhong, Wenshao
    Wu, Xingbo
    PROCEEDINGS OF THE SEVENTEENTH EUROPEAN CONFERENCE ON COMPUTER SYSTEMS (EUROSYS '22), 2022, : 51 - 68
  • [48] SKVM: Scaling In-Memory Key-Value Store on Multicore
    Zheng, Ran
    Wang, Wenjin
    Jin, Hai
    Zhang, Qin
    2015 IEEE SYMPOSIUM ON COMPUTERS AND COMMUNICATION (ISCC), 2015, : 601 - 606
  • [49] FASTER: A Concurrent Key-Value Store with In-Place Updates
    Chandramouli, Badrish
    Prasaad, Guna
    Kossmann, Donald
    Levandoski, Justin
    Hunter, James
    Barnett, Mike
    SIGMOD'18: PROCEEDINGS OF THE 2018 INTERNATIONAL CONFERENCE ON MANAGEMENT OF DATA, 2018, : 275 - 290
  • [50] Rethinking key-value store for parallel I/O optimization
    Kougkas, Anthony
    Eslami, Hassan
    Sun, Xian-He
    Thakur, Rajeev
    Gropp, William
    INTERNATIONAL JOURNAL OF HIGH PERFORMANCE COMPUTING APPLICATIONS, 2017, 31 (04): : 335 - 356