高级搜索

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

隐私保护密文检索技术研究进展

迟佳琳 冯登国 张敏 姜皞昊 吴阿新 孙天齐

迟佳琳, 冯登国, 张敏, 姜皞昊, 吴阿新, 孙天齐. 隐私保护密文检索技术研究进展[J]. 电子与信息学报, 2024, 46(5): 1546-1569. doi: 10.11999/JEIT231300
引用本文: 迟佳琳, 冯登国, 张敏, 姜皞昊, 吴阿新, 孙天齐. 隐私保护密文检索技术研究进展[J]. 电子与信息学报, 2024, 46(5): 1546-1569. doi: 10.11999/JEIT231300
CHI Jialin, FENG Dengguo, ZHANG Min, JIANG Haohao, WU Axin, SUN Tianqi. Advances in Privacy-Preserving Ciphertext Retrieval[J]. Journal of Electronics & Information Technology, 2024, 46(5): 1546-1569. doi: 10.11999/JEIT231300
Citation: CHI Jialin, FENG Dengguo, ZHANG Min, JIANG Haohao, WU Axin, SUN Tianqi. Advances in Privacy-Preserving Ciphertext Retrieval[J]. Journal of Electronics & Information Technology, 2024, 46(5): 1546-1569. doi: 10.11999/JEIT231300

隐私保护密文检索技术研究进展

doi: 10.11999/JEIT231300
基金项目: 国家重点研发计划(2022YFB4501500, 2022YFB4501503)
详细信息
    作者简介:

    迟佳琳:女,博士,助理研究员,研究方向为可搜索加密

    冯登国:男,中国科学院院士,研究员,研究方向为网络与信息安全

    张敏:女,博士,研究员,研究方向为数据安全与隐私保护

    姜皞昊:男,博士生,研究方向为同态加密技术

    吴阿新:男,博士后,研究方向为访问控制与可搜索加密

    孙天齐:男,博士生,研究方向为可搜索加密

    通讯作者:

    张敏 zhangmin@iscas.ac.cn

  • 中图分类号: TN918; TP393

Advances in Privacy-Preserving Ciphertext Retrieval

Funds: The National Key R&D Program of China (2022YFB4501500, 2022YFB4501503)
  • 摘要: 密文检索技术旨在提供密态数据查询服务,提高密文数据的可用性。但目前大多数机制仍存在不同程度的额外信息泄露,容易被攻击者捕获用于恢复明文信息与查询条件。如何强化密文检索中的隐私保护特性,实现信息泄露最小化已成为研究者关注的重点目标。近年来,随着硬件芯片技术与新型密码技术的快速发展,隐私保护密文检索研究方面涌现出了一批新成果,该文主要围绕多样化密文检索、基于可信执行环境的密文检索、隐匿信息检索等研究热点展开阐述,并总结了未来发展趋势。
  • 图  1  可搜索加密系统部署图

    图  2  基于Voronoi图的安全K近邻查询方案[45]示意图

    图  3  基于聚类的安全近似K近邻查询方案[47]示意图

    图  4  基于LSH的安全近似最近邻查询方案[48]示意图

    图  5  半盲化R树索引结构示意图

    图  6  基于SGX的可搜索加密架构示意图

    图  7  基于SGX的布尔检索方案[71]示意图

    图  8  3种典型的基于SGX平台的密文数据库体系结构

    图  9  EnclaveDB[80]架构示意图

    图  10  StealthDB架构与查询处理流程示意图

    图  11  基于同态加密的cPIR基本框架

    图  12  OnionPIR的基本框架(以数据库表示为3维为例)

    图  13  标量版本的Regev加密和矩阵版本的Regev加密对比

    图  14  SimplePIR方案[94]示意图

    图  15  Keyword PIR协议高层框架示意图

    图  16  Pantheon[98]步骤示意图

    图  17  基于DPF的2-服务器PIR协议示意图

    表  1  PIR技术比较

    安全性假设查询尺寸响应尺寸计算量
    XPIR[88]基于Ring-LWE困难性假设$ O\left(\sqrt[d]{n}\right) $$ O\left({F}^{d-1}\right) $$ O\left(n\right) $
    SealPIR[90]基于Ring-LWE困难性假设$ O(\sqrt[d]{n}/N) $$ O\left({F}^{d-1}\right) $
    OnionPIR[92]基于Ring-LWE困难性假设$ O(\sqrt[d]{n}/N) $$ O\left(1\right) $
    SimplePIR[94]基于LWE困难性假设$ O\left(\sqrt{n}\right) $$ O\left(\sqrt{n}\right) $
    FrodoPIR[95]基于LWE困难性假设$ O\left(n\right) $$ O\left(1\right) $
    PIANO PIR[96]统计安全$ O\left(\sqrt{n}\right) $$ O\left(1\right) $$ O\left(\sqrt{n}\right) $
    下载: 导出CSV
  • [1] CURTMOLA R, GARAY J, KAMARA S, et al. Searchable symmetric encryption: Improved definitions and efficient constructions[C]. The 13th ACM Conference on Computer and Communications Security, Alexandria, USA, 2006: 79–88. doi: 10.1145/1180405.1180417.
    [2] ISLAM M S, KUZU M, and KANTARCIOGLU M. Access pattern disclosure on searchable encryption: Ramification, attack and mitigation[C]. The 19th Annual Network and Distributed System Security Symposium, San Diego, USA, 2012: 12.
    [3] LIU Chang, ZHU Liehuang, WANG Mingzhong, et al. Search pattern leakage in searchable encryption: Attacks and new construction[J]. Information Sciences, 2014, 265: 176–188. doi: 10.1016/j.ins.2013.11.021.
    [4] CASH D, GRUBBS P, PERRY J, et al. Leakage-abuse attacks against searchable encryption[C]. The 22nd ACM SIGSAC Conference on Computer and Communications Security, Denver, USA, 2015: 668–679. doi: 10.1145/2810103.2813700.
    [5] NAVEED M, KAMARA S, and WRIGHT C V. Inference attacks on property-preserving encrypted databases[C]. The 22nd ACM SIGSAC Conference on Computer and Communications Security, Denver, USA, 2015: 644–655. doi: 10.1145/2810103.2813651.
    [6] POULIOT D and WRIGHT C V. The shadow nemesis: Inference attacks on efficiently deployable, efficiently searchable encryption[C]. The 2016 ACM SIGSAC Conference on Computer and Communications Security, Vienna, Austria, 2016: 1341–1352. doi: 10.1145/2976749.2978401.
    [7] GRUBBS P, SEKNIQI K, BINDSCHAEDLER V, et al. Leakage-abuse attacks against order-revealing encryption[C]. The 2017 IEEE Symposium on Security and Privacy, San Jose, USA, 2017: 655–672. doi: 10.1109/SP.2017.44.
    [8] VAN ROMPAY C, MOLVA R, and ÖNEN M. A leakage-abuse attack against multi-user searchable encryption[J]. Proceedings on Privacy Enhancing Technologies, 2017, 2017(3): 168–178. doi: 10.1515/popets-2017-0034.
    [9] GRUBBS P, LACHARITÉ M S, MINAUD B, et al. Pump up the volume: Practical database reconstruction from volume leakage on range queries[C]. The 2018 ACM SIGSAC Conference on Computer and Communications Security, Toronto, Canada, 2018: 315–331. doi: 10.1145/3243734.3243864.
    [10] BLACKSTONE L, KAMARA S, and MOATAZ T. Revisiting leakage abuse attacks[C]. The 27th Annual Network and Distributed System Security Symposium, San Diego, USA, 2020: 1–18.
    [11] PODDAR R, WANG S, LU Jianan, et al. Practical volume-based attacks on encrypted databases[C]. The 2020 IEEE European Symposium on Security and Privacy, Genoa, Italy, 2020: 354–369. doi: 10.1109/EuroSP48549.2020.00030.
    [12] KORNAROPOULOS E M, PAPAMANTHOU C, and TAMASSIA R. Response-hiding encrypted ranges: Revisiting security via parametrized leakage-abuse attacks[C]. The 2021 IEEE Symposium on Security and Privacy, San Francisco, USA, 2021: 1502–1519. doi: 10.1109/SP40001.2021.00044.
    [13] NING Jianting, HUANG Xinyi, POH G S, et al. LEAP: Leakage-abuse attack on efficiently deployable, efficiently searchable encryption with partially known dataset[C]. The 2021 ACM SIGSAC Conference on Computer and Communications Security, Online Event, Republic of Korea, 2021: 2307–2320. doi: 10.1145/3460120.3484540.
    [14] OYA S and KERSCHBAUM F. Hiding the access pattern is not enough: Exploiting search pattern leakage in searchable encryption[C/OL]. The 30th USENIX Security Symposium, 2021: 127–142.
    [15] LAMBREGTS S, CHEN Huanhuan, NING Jianting, et al. VAL: Volume and access pattern leakage-abuse attack with leaked documents[C]. The 27th European Symposium on Research in Computer Security, Copenhagen, Denmark, 2022: 653–676. doi: 10.1007/978-3-031-17140-6_32.
    [16] KELLARIS G, KOLLIOS G, NISSIM K, et al. Generic attacks on secure outsourced databases[C]. The 2016 ACM SIGSAC Conference on Computer and Communications Security, Vienna, Austria, 2016: 1329–1340. doi: 10.1145/2976749.2978386.
    [17] LACHARITÉ M S, MINAUD B, and PATERSON K G. Improved reconstruction attacks on encrypted data using range query leakage[C]. The 2018 IEEE Symposium on Security and Privacy, San Francisco, USA, 2018: 297–314. doi: 10.1109/SP.2018.00002.
    [18] ZHANG Yupeng, KATZ J, and PAPAMANTHOU C. All your queries are belong to us: The power of file-injection attacks on searchable encryption[C]. The 25th USENIX Conference on Security Symposium, Austin, USA, 2016: 707–720.
    [19] 王贇玲, 陈晓峰. 对称可搜索加密技术研究进展[J]. 电子与信息学报, 2020, 42(10): 2374–2385. doi: 10.11999/JEIT190890.

    WANG Yunling and CHEN Xiaofeng. Research on searchable symmetric encryption[J]. Journal of Electronics & Information Technology, 2020, 42(10): 2374–2385. doi: 10.11999/JEIT190890.
    [20] REN Kui and WANG Cong. Searchable Encryption: From Concepts to Systems[M]. Cham: Springer, 2023: 11–12. doi: 10.1007/978-3-031-21377-9.
    [21] 刘文心, 高莹. 对称可搜索加密的安全性研究进展[J]. 信息安全学报, 2021, 6(2): 73–84. doi: 10.19363/J.cnki.cn10-1380/tn.2021.03.05.

    LIU Wenxin and GAO Ying. A survey on security development of searchable symmetric encryption[J]. Journal of Cyber Security, 2021, 6(2): 73–84. doi: 10.19363/J.cnki.cn10-1380/tn.2021.03.05.
    [22] 黄一才, 李森森, 郁滨. 云环境下对称可搜索加密研究综述[J]. 电子与信息学报, 2023, 45(3): 1134–1146. doi: 10.11999/JEIT211572.

    HUANG Yicai, LI Sensen, and YU Bin. A survey of symmetric searchable encryption in cloud environment[J]. Journal of Electronics & Information Technology, 2023, 45(3): 1134–1146. doi: 10.11999/JEIT211572.
    [23] ZHANG Xianglong, WANG Wei, XU Peng, et al. High recovery with fewer injections: Practical binary volumetric injection attacks against dynamic searchable encryption[C]. The 32nd USENIX Conference on Security Symposium, Anaheim, USA, 2023: 333.
    [24] CHEN Tianyang, XU Peng, PICEK S, et al. The power of bamboo: On the post-compromise security for searchable symmetric encryption[C]. The 30th Annual Network and Distributed System Security Symposium, San Diego, USA, 2023.
    [25] BRAKERSKI Z and VAIKUNTANATHAN V. Efficient fully homomorphic encryption from (standard) LWE[C]. The IEEE 52nd Annual Symposium on Foundations of Computer Science, Palm Springs, USA, 2011: 97–106. doi: 10.1109/FOCS.2011.12.
    [26] FAN Junfeng and VERCAUTEREN F. Somewhat practical fully homomorphic encryption[J]. Cryptology ePrint Archive, 2012: 144.
    [27] BRAKERSKI Z, GENTRY C, and VAIKUNTANATHAN V. (Leveled) fully homomorphic encryption without bootstrap[J]. ACM Transactions on Computation Theory, 2014, 6(3): 13. doi: 10.1145/2633600.
    [28] GENTRY C, SAHAI A, and WATERS B. Homomorphic encryption from learning with errors: Conceptually-simpler, asymptotically-faster, attribute-based[C]. The 33rd Annual Cryptology Conference, Santa Barbara, USA, 2013: 75–92. doi: 10.1007/978-3-642-40041-4_5.
    [29] PAILLIER P. Public-key cryptosystems based on composite degree residuosity classes[C]. The 17th International Conference on the Theory and Applications of Cryptographic Techniques, Prague, Czech Republic, 1999: 223–238. doi: 10.1007/3-540-48910-X_16.
    [30] RIVEST R L, SHAMIR A, and ADLEMAN L. A method for obtaining digital signatures and public-key cryptosystems[J]. Communications of the ACM, 1978, 21(2): 120–126. doi: 10.1145/359340.359342.
    [31] GOLDREICH O and OSTROVSKY R. Software protection and simulation on oblivious RAMs[J]. Journal of the ACM, 1996, 43(3): 431–473. doi: 10.1145/233551.233553.
    [32] 吴鹏飞, 沈晴霓, 秦嘉, 等. 不经意随机访问机研究综述[J]. 软件学报, 2018, 29(9): 2753–2777. doi: 10.13328/j.cnki.jos.005591.

    WU Pengfei, SHEN Qingni, QIN Jia, et al. Survey of oblivious RAM[J]. Journal of Software, 2018, 29(9): 2753–2777. doi: 10.13328/j.cnki.jos.005591.
    [33] STEFANOV E, VAN DIJK M, SHI E, et al. Path ORAM: An extremely simple oblivious RAM protocol[C]. The 2013 ACM SIGSAC Conference on Computer & Communications Security, Berlin, Germany, 2013: 299–310. doi: 10.1145/2508859.2516660.
    [34] REN Ling, FLETCHER C W, KWON A, et al. Ring ORAM: Closing the gap between small and large client storage oblivious RAM[J]. IACR Cryptology ePrint Archive, 2014, 2014: 997.
    [35] YU Xiangyao, HAIDER S K, REN Ling, et al. PrORAM: Dynamic prefetcher for oblivious RAM[C]. ACM/IEEE 42nd Annual International Symposium on Computer Architecture, Portland, USA, 2015: 616–628. doi: 10.1145/2749469.2750413.
    [36] WANG Xiao, CHAN H, and SHI E. Circuit ORAM: On tightness of the goldreich-ostrovsky lower bound[C]. The 22nd ACM SIGSAC Conference on Computer and Communications Security, Denver, USA, 2015: 850–861. doi: 10.1145/2810103.2813634.
    [37] WANG Wenhao, CHEN Guoxing, PAN Xiaorui, et al. Leaky cauldron on the dark land: Understanding memory side-channel hazards in SGX[C]. The 2017 ACM SIGSAC Conference on Computer and Communications Security, Dallas, USA, 2017: 2421–2434. doi: 10.1145/3133956.3134038.
    [38] CHECKOWAY S and SHACHAM H. Iago attacks: Why the system call API is a bad untrusted RPC interface[J]. ACM SIGARCH Computer Architecture News, 2013, 41(1): 253–264. doi: 10.1145/2490301.2451145.
    [39] WONG W K, CHEUNG S W L, KAO Ben, et al. Secure kNN computation on encrypted databases[C]. The 2009 ACM SIGMOD International Conference on Management of Data, Providence, USA, 2009: 139–152. doi: 10.1145/1559845.1559862.
    [40] WANG Boyang, HOU Yantian, and LI Ming. Practical and secure nearest neighbor search on encrypted large-scale data[C]. IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications, San Francisco, USA, 2016: 1–9. doi: 10.1109/INFOCOM.2016.7524389.
    [41] YAO Bin, LI Feifei, and XIAO Xiaokui. Secure nearest neighbor revisited[C]. IEEE 29th International Conference on Data Engineering, Brisbane, Australia, 2013: 733–744. doi: 10.1109/ICDE.2013.6544870.
    [42] LEI Xinyu, LIU A X, LI Rui, et al. SecEQP: A secure and efficient scheme for SkNN query problem over encrypted geodata on cloud[C]. IEEE 35th International Conference on Data Engineering, Macao, China, 2019: 662–673. doi: 10.1109/ICDE.2019.00065.
    [43] LI Rui and LIU A X. Adaptively secure conjunctive query processing over encrypted data for cloud computing[C]. IEEE 33rd International Conference on Data Engineering, San Diego, USA, 2017: 697–708. doi: 10.1109/ICDE.2017.122.
    [44] ELMEHDWI Y, SAMANTHULA B K, and JIANG Wei. Secure k-nearest neighbor query over encrypted data in outsourced environments[C]. IEEE 30th International Conference on Data Engineering, Chicago, USA, 2014: 664–675. doi: 10.1109/ICDE.2014.6816690.
    [45] CUI Ningning, YANG Xiaochun, WANG Bin, et al. SVkNN: Efficient secure and verifiable k-nearest neighbor query on the cloud platform[C]. IEEE 36th International Conference on Data Engineering, Dallas, USA, 2020: 253–264. doi: 10.1109/ICDE48307.2020.00029.
    [46] HJALTASON G R and SAMET H. Distance browsing in spatial databases[J]. ACM Transactions on Database Systems, 1999, 24(2): 265–318. doi: 10.1145/320248.320255.
    [47] CHEN Hao, CHILLOTTI I, DONG Yihe, et al. SANNS: Scaling up secure approximate k-nearest neighbors search[C/OL]. The 29th USENIX Security Symposium, Online Event, 2020: 2111–2128.
    [48] SERVAN-SCHREIBER S, LANGOWSKI S, and DEVADAS S. Private approximate nearest neighbor search with sublinear communication[C]. The 2022 IEEE Symposium on Security and Privacy, San Francisco, USA, 2022: 911–929. doi: 10.1109/SP46214.2022.9833702.
    [49] PENG Yanguo, CUI Jiangtao, LI Hui, et al. A reusable and single-interactive model for secure approximate k-nearest neighbor query in cloud[J]. Information Sciences, 2017, 387: 146–164. doi: 10.1016/j.ins.2016.07.069.
    [50] BOLDYREVA A and TANG Tianxin. Privacy-preserving approximate k-nearest-neighbors search that hides access, query and volume patterns[J]. Proceedings on Privacy Enhancing Technologies, 2021, 2021(4): 549–574. doi: 10.2478/popets-2021-0084.
    [51] LIU Jinfei, YANG Juncheng, XIONG Li, et al. Secure skyline queries on cloud platform[C]. IEEE 33rd International Conference on Data Engineering, San Diego, USA, 2017: 633–644. doi: 10.1109/ICDE.2017.117.
    [52] WANG Zuan, DING Xiaofeng, JIN Hai, et al. Efficient secure and verifiable location-based skyline queries over encrypted data[J]. Proceedings of the VLDB Endowment, 2022, 15(9): 1822–1834. doi: 10.14778/3538598.3538605.
    [53] ZEIGHAMI S, GHINITA G, and SHAHABI C. Secure dynamic skyline queries using result materialization[C]. IEEE 37th International Conference on Data Engineering, Chania, Greece, 2021: 157–168. doi: 10.1109/ICDE51399.2021.00021.
    [54] HAHN F, LOZA N, and KERSCHBAUM F. Practical and secure substring search[C]. The 2018 International Conference on Management of Data, Houston, USA, 2018: 163–176. doi: 10.1145/3183713.3183754.
    [55] FU Zhangjie, HUANG Fengxiao, REN Kui, et al. Privacy-preserving smart semantic search based on conceptual graphs over encrypted outsourced data[J]. IEEE Transactions on Information forensics and Security, 2017, 12(8): 1874–1884. doi: 10.1109/TIFS.2017.2692728.
    [56] XU Lyu, JIANG Jiaxin, CHOI B, et al. Privacy preserving strong simulation queries on large graphs[C]. IEEE 37th International Conference on Data Engineering, Chania, Greece, 2021: 1500–1511. doi: 10.1109/ICDE51399.2021.00133.
    [57] FUHRY B, BAHMANI R, BRASSER F, et al. HardIDX: Practical and secure index with SGX[C]. The 31st IFIP Annual Conference on Data and Applications Security and Privacy, Philadelphia, USA, 2017: 386–408. doi: 10.1007/978-3-319-61176-1_22.
    [58] XU Jian, ZHANG Yuanjing, FU Kuiyuan, et al. SGX-based secure indexing system[J]. IEEE Access, 2019, 7: 77923–77931. doi: 10.1109/ACCESS.2019.2921223.
    [59] FERREIRA B, PORTELA B, OLIVEIRA T, et al. Boolean searchable symmetric encryption with filters on trusted hardware[J]. IEEE Transactions on Dependable and Secure Computing, 2022, 19(2): 1307–1319. doi: 10.1109/TDSC.2020.3012100.
    [60] SHAON F and KANTARCIOGLU M. SGX-IR: Secure information retrieval with trusted processors[C]. The 34th IFIP Annual Conference on Data and Applications Security and Privacy, Regensburg, Germany, 2020: 367–387. doi: 10.1007/978-3-030-49669-2_21.
    [61] JIANG Qin, CHANG E C, QI Yong, et al. Rphx: Result pattern hiding conjunctive query over private compressed index using intel SGX[J]. IEEE Transactions on Information Forensics and Security, 2022, 17: 1053–1068. doi: 10.1109/TIFS.2022.3144877.
    [62] CHEN Yaxing, ZHENG Qinghua, YAN Zheng, et al. QShield: Protecting outsourced cloud data queries with multi-user access control based on SGX[J]. IEEE Transactions on Parallel and Distributed Systems, 2021, 32(2): 485–499. doi: 10.1109/TPDS.2020.3024880.
    [63] AMJAD G, KAMARA S, and MOATAZ T. Forward and backward private searchable encryption with SGX[C]. Proceedings of the 12th European Workshop on Systems Security, Dresden, Germany, 2019: 4. doi: 10.1145/3301417.3312496.
    [64] VO V, LAI Shangqi, YUAN Xingliang, et al. Towards efficient and strong backward private searchable encryption with secure enclaves[C]. The 19th International Conference on Applied Cryptography and Network Security, Kamakura, Japan, 2021: 50–75. doi: 10.1007/978-3-030-78372-3_3.
    [65] YOON H, MOON S, KIM Y, et al. SPEKS: Forward private SGX-based public key encryption with keyword search[J]. Applied Sciences, 2020, 10(21): 7842. doi: 10.3390/app10217842.
    [66] HUANG Yanyu, LV Siyi, LIU Zheli, et al. Cetus: An efficient symmetric searchable encryption against file-injection attack with SGX[J]. Science China Information Sciences, 2021, 64(8): 182314. doi: 10.1007/s11432-020-3039-x.
    [67] MISHRA P, PODDAR R, CHEN J, et al. Oblix: An efficient oblivious search index[C]. The 2018 IEEE Symposium on Security and Privacy, San Francisco, USA, 2018: 279–296. doi: 10.1109/SP.2018.00045.
    [68] OHRIMENKO O, SCHUSTER F, FOURNET C, et al. Oblivious multi-party machine learning on trusted processors[C]. The 25th USENIX Conference on Security Symposium, Austin, USA, 2016: 619–636.
    [69] PODDAR R, ANANTHANARAYANAN G, SETTY S, et al. Visor: Privacy-preserving video analytics as a cloud service[C/OL]. The 29th USENIX Conference on Security Symposium, 2020: 59.
    [70] LIU Chang, WANG X S, NAYAK K, et al. ObliVM: A programming framework for secure computation[C]. The 2015 IEEE Symposium on Security and Privacy, San Jose, USA, 2015: 359–376. doi: 10.1109/SP.2015.29.
    [71] JIANG Qin, QI Yong, QI Saiyu, et al. Pbsx: A practical private boolean search using Intel SGX[J]. Information Sciences, 2020, 521: 174–194. doi: 10.1016/j.ins.2020.02.031.
    [72] SASY S, GORBUNOV S, and FLETCHER C W. ZeroTrace: Oblivious memory primitives from Intel SGX[C]. The 25th Annual Network and Distributed System Security Symposium, San Diego, USA, 2018: 1–15.
    [73] MAINARDI N, SAMPIETRO D, BARENGHI A, et al. Efficient oblivious substring search via architectural support[C]. The 36th Annual Computer Security Applications Conference, Austin, USA, 2020: 526–541. doi: 10.1145/3427228.3427296.
    [74] POPA R A, REDFIELD C M S, ZELDOVICH N, et al. CryptDB: Protecting confidentiality with encrypted query processing[C]. The 23rd ACM Symposium on Operating Systems Principles, Cascais, Portugal, 2011: 85–100. doi: 10.1145/2043556.2043566.
    [75] REN Xuanle, SU Le, GU Zhen, et al. HEDA: Multi-attribute unbounded aggregation over homomorphically encrypted database[J]. Proceedings of the VLDB Endowment, 2022, 16(4): 601–614. doi: 10.14778/3574245.3574248.
    [76] BATER J, ELLIOTT G, EGGEN C, et al. SMCQL: Secure querying for federated databases[J]. Proceedings of the VLDB Endowment, 2017, 10(6): 673–684. doi: 10.14778/3055330.3055334.
    [77] ZHOU Wenchao, CAI Yifan, PENG Yanqing, et al. VeriDB: An SGX-based verifiable database[C]. The 2021 International Conference on Management of Data, Online Event, China, 2021: 2182–2194. doi: 10.1145/3448016.3457308.
    [78] PARK J, KANG N, KIM T, et al. Nested enclave: Supporting fine-grained hierarchical isolation with SGX[C]. The ACM/IEEE 47th Annual International Symposium on Computer Architecture, Valencia, Spain, 2020: 776–789. doi: 10.1109/ISCA45697.2020.00069.
    [79] GU Jinyu, ZHU Bojun, LI Mingyu, et al. A hardware-software co-design for efficient intra-enclave isolation[C]. The 31st USENIX Security Symposium, Boston, USA, 2022: 3129–3145.
    [80] PRIEBE C, VASWANI K, and COSTA M. EnclaveDB: A secure database using SGX[C]. The 2018 IEEE Symposium on Security and Privacy, San Francisco, USA, 2018: 264–278. doi: 10.1109/SP.2018.00025.
    [81] VINAYAGAMURTHY D, GRIBOV A, and GORBUNOV S. StealthDB: A scalable encrypted database with full SQL query support[J]. Proceedings of Privacy Enhancing Technologies, 2019, 2019(3): 370–388. doi: 10.2478/popets-2019-0052.
    [82] ANTONOPOULOS P, ARASU A, SINGH K D, et al. Azure SQL database always encrypted[C/OL]. The 2020 ACM SIGMOD International Conference on Management of Data, Portland, USA, 2020: 1511–1525. doi: 10.1145/3318464.3386141.
    [83] WANG Sheng, LI Yiran, LI Huorong, et al. Operon: An encrypted database for ownership-preserving data management[J]. Proceedings of the VLDB Endowment, 2022, 15(12): 3332–3345. doi: 10.14778/3554821.3554826.
    [84] ZHENG Wenting, DAVE A, BEEKMAN J G, et al. Opaque: An oblivious and encrypted distributed analytics platform[C]. The 14th USENIX Conference on Networked Systems Design and Implementation, Boston, USA, 2017: 283–298.
    [85] ESKANDARIAN S and ZAHARIA M. ObliDB: Oblivious query processing for secure databases[J]. Proceedings of the VLDB Endowment, 2019, 13(2): 169–183. doi: 10.14778/3364324.3364331.
    [86] CROOKS N, BURKE M, CECCHETTI E, et al. Obladi: Oblivious serializable transactions in the cloud[C]. The 13th USENIX Symposium on Operating Systems Design and Implementation, Carlsbad, USA, 2018: 727–743.
    [87] MENON S J and WU D J. SPIRAL: Fast, high-rate single-server PIR via FHE composition[C]. The 2022 IEEE Symposium on Security and Privacy (SP), San Francisco, USA, 2022: 930–947. doi: 10.1109/SP46214.2022.9833700.
    [88] AGUILAR-MELCHOR C, BARRIER J, FOUSSE L, et al. XPIR: Private information retrieval for everyone[J]. Proceedings on Privacy Enhancing Technologies (PETS), 2016, 2016(1): 155–174.
    [89] STERN J P. A new and efficient all-or-nothing disclosure of secrets protocol[C]. The International Conference on the Theory and Application of Cryptology and Information Security, Beijing, China, 1998: 357–371. doi: 10.1007/3-540-49649-1_28.
    [90] ANGEL S, CHEN Hao, LAINE K, et al. PIR with compressed queries and amortized query processing[C]. 2018 IEEE Symposium on Security and Privacy (SP), San Francisco, USA, 2018: 962–979. doi: 10.1109/SP.2018.00062.
    [91] ISHAI Y, KUSHILEVITZ E, OSTROVSKY R, et al. Batch codes and their applications[C]. The 36th Annual ACM Symposium on Theory of Computing, Chicago, USA, 2004: 262–271. doi: 10.1145/1007352.1007396.
    [92] MUGHEES M H, CHEN Hao, and REN Ling. OnionPIR: Response efficient single-server PIR[C]. The 2021 ACM SIGSAC Conference on Computer and Communications Security, Virtual Event, Republic of Korea, 2021: 2292–2306. doi: 10.1145/3460120.3485381.
    [93] GENTRY G and HALEVI S. Compressible FHE with applications to PIR[C]. The 17th Theory of Cryptography Conference, Nuremberg, Germany, 2019: 438–464. doi: 10.1007/978-3-030-36033-7_17.
    [94] HENZINGER A, HONG M M, CORRIGAN-GIBBS H, et al. One server for the price of two: Simple and fast single-server private information retrieval[C]. The 32nd USENIX Conference on Security Symposium, Anaheim, USA, 2023: 218.
    [95] DAVIDSON A, PESTANA G, and CELI S. FrodoPIR: Simple, scalable, single-server private information retrieval[J]. Proceedings on Privacy Enhancing Technologies (PETS), 2023, 2023(1): 365–383. doi: 10.56553/popets-2023-0022.
    [96] ZHOU Mingxun, PARK A, SHI E, et al. Piano: Extremely simple, single-server PIR with sublinear server computation[C]. The 45th IEEE Symposium on Security and Privacy, San Francisco, USA, 2024.
    [97] MAHDAVI R A and KERSCHBAUM F. Constant-weight PIR: Single-round keyword PIR via constant-weight equality operators[C]. The 31st USENIX Security Symposium, Boston, USA, 2022: 1723–1740.
    [98] AHMAD I, AGRAWAL D, ABBADI A E, et al. Pantheon: Private retrieval from public key-value store[J]. Proceedings of the VLDB Endowment, 2022, 16(4): 643–656. doi: 10.14778/3574245.3574251.
    [99] ISHAI Y and PASKIN A. Evaluating branching programs on encrypted data[C]. The 4th Theory of Cryptography Conference, Amsterdam, The Netherlands, 2007: 575–594. doi: 10.1007/978-3-540-70936-7_31.
    [100] GARG S, HAJIABADI M, and OSTROVSKY R. Efficient range-trapdoor functions and applications: Rate-1 OT and more[C]. Proceedings of the 18th Theory of Cryptography Conference, Durham, USA, 2020: 88–116. doi: 10.1007/978-3-030-64375-1_4.
    [101] CHASE M, GARG S, HAJIABADI M, et al. Amortizing rate-1 OT and applications to PIR and PSI[C]. The 19th Theory of Cryptography Conference, Raleigh, USA, 2021: 126–156. doi: 10.1007/978-3-030-90456-2_5.
    [102] LIU Jian, LI Jingyu, WU Di, et al. PIRANA: Faster multi-query PIR via constant-weight codes[J]. 2024 IEEE Symposium on Security and Privacy (SP), 2024: 43. doi: 10.1109/SP54263.2024.00039.
    [103] PATEL S, SEO J Y, and YEO K. Don't be dense: Efficient keyword PIR for sparse databases[J]. IACR Cryptology ePrint Archive, 2023, 2023: 466.
    [104] CHOR B, KUSHILEVITZ E, GOLDREICH O, et al. Private information retrieval[J]. Journal of the ACM, 1998, 45(6): 965–981. doi: 10.1145/293347.293350.
    [105] AMBAINIS A. Upper bound on the communication complexity of private information retrieval[C]. The 24th International Colloquium on Automata, Languages, and Programming, Bologna, Italy, 1997: 401–407. doi: 10.1007/3-540-63165-8_196.
    [106] BEIMEL A, ISHAI Y, KUSHILEVITZ E, et al. Breaking the O(n1/(2k-1)) barrier for information-theoretic private information retrieval[C]. The 43rd Annual IEEE Symposium on Foundations of Computer Science, Vancouver, Canada, 2002: 261–270. doi: 10.1109/SFCS.2002.1181949.
    [107] BEIMEL A and STAHL Y. Robust information-theoretic private information retrieval[J]. Journal of Cryptology, 2007, 20(3): 295–321. doi: 10.1007/s00145-007-0424-2.
    [108] REED I S and SOLOMON G. Polynomial codes over certain finite fields[J]. Journal of the Society for Industrial and Applied Mathematics, 1960, 8(2): 300–304. doi: 10.1137/0108018.
    [109] ERIGUCHI R, KUROSAWA K, and NUIDA K. Multi-server PIR with full error detection and limited error correction[C]. The 3rd Conference on Information-Theoretic Cryptography, Cambridge, USA, 2022: 1: 1–1: 20.
    [110] KATZ J and TREVISAN L. On the efficiency of local decoding procedures for error-correcting codes[C]. The 32nd Annual ACM Symposium on Theory of Computing, Portland, USA, 2000: 80–86. doi: 10.1145/335305.335315.
    [111] YEKHANIN S. Towards 3-query locally decodable codes of subexponential length[J]. Journal of the ACM, 2008, 55(1): 1. doi: 10.1145/1326554.1326555.
    [112] EFREMENKO K. 3-query locally decodable codes of subexponential length[C]. The 41st Annual ACM Symposium on Theory of Computing, Bethesda, USA, 2009: 39–44. doi: 10.1145/1536414.1536422.
    [113] GROLMUSZ V. Superpolynomial size set-systems with restricted intersections mod 6 and explicit Ramsey graphs[J]. Combinatorica, 2000, 20(1): 71–86. doi: 10.1007/s004930070032.
    [114] DVIR Z and GOPI S. 2-server PIR with subpolynomial communication[J]. Journal of the ACM, 2016, 63(4): 39. doi: 10.1145/2968443.
    [115] BEIMEL A, ISHAI Y, KUSHILEVITZ E, et al. Share conversion and private information retrieval[C]. IEEE 27th Conference on Computational Complexity, Porto, Portugal, 2012: 258–268. doi: 10.1109/CCC.2012.23.
    [116] GILBOA N and ISHAI Y. Distributed point functions and their applications[C]. The 33rd Annual International Conference on the Theory and Applications of Cryptographic Techniques, Copenhagen, Denmark, 2014: 640–658. doi: 10.1007/978-3-642-55220-5_35.
    [117] BOYLE E, GILBOA N, and ISHAI Y. Function secret sharing[C]. The 34th Annual International Conference on the Theory and Applications of Cryptographic Techniques, Sofia, Bulgaria, 2015: 337–367. doi: 10.1007/978-3-662-46803-6_12.
    [118] BATER J, HE Xi, EHRICH W, et al. Shrinkwrap: Efficient SQL query processing in differentially private data federations[J]. Proceedings of the VLDB Endowment, 2018, 12(3): 307–320. doi: 10.14778/3291264.3291274.
    [119] QIN Lianke, JAYARAM R, SHI E, et al. Adore: Differentially oblivious relational database operators[J]. Proceedings of the VLDB Endowment, 2022, 16(4): 842–855. doi: 10.14778/3574245.3574267.
  • 加载中
图(17) / 表(1)
计量
  • 文章访问数:  683
  • HTML全文浏览量:  396
  • PDF下载量:  162
  • 被引次数: 0
出版历程
  • 收稿日期:  2023-11-24
  • 修回日期:  2024-05-07
  • 网络出版日期:  2024-05-15
  • 刊出日期:  2024-05-30

目录

    /

    返回文章
    返回