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Efficient Secure Computation of Order-Preserving Encryption

Published: 05 October 2020 Publication History

Abstract

Order-preserving encryption (OPE) allows encrypting data, while still enabling efficient range queries on the encrypted data. Moreover, it does not require any change to the database management system, which makes OPE schemes very suitable for data outsourcing with threats from weak adversaries. However, all OPE schemes are necessarily symmetric limiting the use case to one client and one server. Imagine a scenario where a Data Owner (DO) outsources encrypted data to the Cloud Service Provider (CSP) and a Data Analyst (DA) wants to execute private range queries on this data. Then either the DO must reveal its encryption key or the DA must reveal the private queries. In this paper, we overcome this limitation by allowing the equivalent of a public-key OPE. We present a secure multiparty protocol that enables secure range queries for multiple users. In this scheme, the DA cooperates with the DO and the CSP in order to order-preserving encrypt the private range queries without revealing any other information to the parties. The basic idea of our scheme is to replace encryption with a secure, interactive protocol. In this protocol, we combine OPE based on binary search trees with homomorphic encryption and garbled circuits (GC) achieving security against passive adversaries with sublinear communication and computation complexity. We apply our construction to different OPE schemes including frequency-hiding OPE and OPE based on an efficiently searchable encrypted data structure which can withstand many of the popularized attacks on OPE. We implemented our scheme and observed that if the database size of the DO has 1 million entries it takes only about 0.3 s on average via a loopback interface (1.3 s via a LAN and 15.6 s via a WAN with about 200 ms round-trip time) to encrypt an input of the DA. Moreover, while the related work has an overhead of 10 to 100 seconds compared to a plaintext MySQL range query on a database with 10 million entries, our scheme has an overhead of only 360 milliseconds.

Supplementary Material

MP4 File (3320269.3384739.mp4)
Order-preserving encryption (OPE) allows encrypting data, while still enabling efficient range queries on the encrypted data. Moreover,\r\nit does not require any change to the database management system, which makes OPE schemes very suitable for data outsourcing with\r\nthreats from weak adversaries. However, all OPE schemes are symmetric limiting the use case to one client and one server.\r\n\r\nImagine a scenario where a Data Owner (DO) outsources encrypted data to the Cloud Service Provider (CSP) and a Data Analyst (DA)\r\nwants to execute private range queries on this data. Then either the DO must reveal its encryption key or the DA must reveal the private\r\nqueries. \r\n\r\nIn this talk, we overcome this limitation by allowing the equivalent of a public-key OPE. We present a secure multiparty protocol that enables secure range queries for multiple users. In this scheme, the parties cooperate to order-preserving encrypt the private range queries without revealing any other information.

References

[1]
Rakesh Agrawal, Jerry Kiernan, Ramakrishnan Srikant, and Yirong Xu. 2004. Order Preserving Encryption for Numeric Data. In SIGMOD. ACM, New York, NY, USA, 563--574.
[2]
Ghous Amjad, Seny Kamara, and Tarik Moataz. 2019. Breach-Resistant Structured Encryption. PoPETs, Vol. 2019, 1 (2019), 245--265.
[3]
Gilad Asharov, Yehuda Lindell, Thomas Schneider, and Michael Zohner. 2013. More Efficient Oblivious Transfer and Extensions for Faster Secure Computation. In CCS '13. ACM, New York, NY, USA, 535--548.
[4]
Mikhail J. Atallah, Marina Bykova, Jiangtao Li, Keith B. Frikken, and Mercan Topkara. 2004. Private collaborative forecasting and benchmarking. In WPES. 103--114.
[5]
Mikhail J. Atallah, Hicham G. Elmongui, Vinayak Deshpande, and Leroy B. Schwarz. 2003. Secure Supply-Chain Protocols. In CEC '03. 293--302.
[6]
Mihir Bellare, Viet Tung Hoang, Sriram Keelveedhi, and Phillip Rogaway. 2013. Efficient Garbling from a Fixed-Key Blockcipher. In SP '13. 478--492.
[7]
Alexandra Boldyreva, Nathan Chenette, Younho Lee, and Adam O'Neill. 2009. Order-Preserving Symmetric Encryption. In EUROCRYPT '09. Springer-Verlag, Berlin, Heidelberg, 224--241.
[8]
Alexandra Boldyreva, Nathan Chenette, and Adam O'Neill. 2011. Order-preserving Encryption Revisited: Improved Security Analysis and Alternative Solutions. In CRYPTO'11. Springer-Verlag, Berlin, Heidelberg, 578--595.
[9]
Octavian Catrina and Florian Kerschbaum. 2008. Fostering the Uptake of Secure Multiparty Computation in E-Commerce. In ARES '08. 693--700.
[10]
Nathan Chenette, Kevin Lewi, Stephen A. Weis, and David J. Wu. 2016. Practical Order-Revealing Encryption with Limited Leakage. In FSE '16. 474--493.
[11]
Ronald Cramer, Ivan Damgård, and Jesper Buus Nielsen. 2015. Secure Multiparty Computation and Secret Sharing .Cambridge University Press, New York, NY, USA.
[12]
Reza Curtmola, Juan Garay, Seny Kamara, and Rafail Ostrovsky. 2006. Searchable Symmetric Encryption: Improved Definitions and Efficient Constructions. In CCS '06. 79--88.
[13]
Ivan Damgård, Martin Geisler, and Mikkel Krøigaard. 2007. Efficient and Secure Comparison for On-Line Auctions. In ACISP. 416--430.
[14]
Ivan Damgård and Rune Thorbek. 2008. Efficient Conversion of Secret-shared Values Between Different Fields. IACR Cryptology ePrint Archive, Vol. 2008 (2008), 221.
[15]
Wenliang Du and Mikhail J. Atallah. 2001. Privacy-Preserving Cooperative Scientific Computations. In CSFW '01. IEEE Computer Society, Washington, DC, USA, 273--.
[16]
Betül Durak, Thomas DuBuisson, and David Cash. 2016. What Else is Revealed by Order-Revealing Encryption? Technical Report 786. IACR Cryptology ePrint Archive.
[17]
Yael Ejgenberg, Moriya Farbstein, Meital Levy, and Yehuda Lindell. 2012. SCAPI: The Secure Computation Application Programming Interface. IACR Cryptology ePrint Archive, Vol. 2012 (2012), 629.
[18]
Craig Gentry. 2009. Fully Homomorphic Encryption Using Ideal Lattices. In STOC '09. ACM, New York, NY, USA, 169--178.
[19]
Oded Goldreich. 2004. Foundations of Cryptography: Volume 2, Basic Applications .Cambridge University Press, New York, NY, USA.
[20]
Paul Grubbs, Kevin Sekniqi, Vincent Bindschaedler, Muhammad Naveed, and Thomas Ristenpart. 2016. Leakage-Abuse Attacks against Order-Revealing Encryption. Technical Report 895. IACR Cryptology ePrint Archive.
[21]
P. Grubbs, K. Sekniqi, V. Bindschaedler, M. Naveed, and T. Ristenpart. 2017. Leakage-Abuse Attacks against Order-Revealing Encryption. In SP '17. 655--672.
[22]
Florian Hahn and Florian Kerschbaum. 2014. Searchable Encryption with Secure and Efficient Updates. In CCS '14. 310--320.
[23]
Yuval Ishai, Eyal Kushilevitz, Steve Lu, and Rafail Ostrovsky. 2016. Private Large-Scale Databases with Distributed Searchable Symmetric Encryption. In CT-RSA (Lecture Notes in Computer Science), Vol. 9610. Springer, 90--107.
[24]
Florian Kerschbaum. 2012. Privacy-Preserving Computation - (Position Paper). In APF '12. 41--54.
[25]
Florian Kerschbaum. 2015. Frequency-Hiding Order-Preserving Encryption. In CCS '15. ACM, New York, NY, USA, 656--667.
[26]
Florian Kerschbaum and Axel Schrö pfer. 2014. Optimal Average-Complexity Ideal-Security Order-Preserving Encryption. In SIGSAC '14. 275--286.
[27]
Florian Kerschbaum and Anselme Tueno. 2019. An Efficiently Searchable Encrypted Data Structure for Range Queries. In ESORICS '19. 344--364.
[28]
Vladimir Kolesnikov, Ahmad-Reza Sadeghi, and Thomas Schneider. 2009. Improved Garbled Circuit Building Blocks and Applications to Auctions and Computing Minima. In CANS '09. 1--20.
[29]
Vladimir Kolesnikov and Thomas Schneider. 2008. Improved Garbled Circuit: Free XOR Gates and Applications. In ICALP '08. 486--498.
[30]
Kevin Lewi and David J. Wu. 2016. Order-Revealing Encryption: New Constructions, Applications, and Lower Bounds. In CCS '16. 1167--1178.
[31]
Yehuda Lindell and Benny Pinkas. 2002. Privacy Preserving Data Mining. Journal of Cryptology, Vol. 15, 3 (2002), 177--206.
[32]
Yehuda Lindell and Benny Pinkas. 2009a. A Proof of Security of Yao's Protocol for Two-Party Computation. J. Cryptol., Vol. 22, 2 (April 2009), 161--188.
[33]
Yehuda Lindell and Benny Pinkas. 2009b. Secure Multiparty Computation for Privacy-Preserving Data Mining. The Journal of Privacy and Confidentiality, Vol. 2009, 1 (2009), 59--98.
[34]
Charalampos Mavroforakis, Nathan Chenette, Adam O'Neill, George Kollios, and Ran Canetti. 2015. Modular Order-Preserving Encryption, Revisited. In SIGMOD '15. 763--777.
[35]
Muhammad Naveed, Seny Kamara, and Charles V. Wright. 2015. Inference Attacks on Property-Preserving Encrypted Databases. In CCS '15. ACM, New York, NY, USA, 644--655.
[36]
Pascal Paillier. 1999. Public-key Cryptosystems Based on Composite Degree Residuosity Classes. In EUROCRYPT'99. Springer-Verlag, Berlin, Heidelberg.
[37]
Rishabh Poddar, Tobias Boelter, and Raluca Ada Popa. 2016. Arx: A Strongly Encrypted Database System. IACR Cryptology ePrint Archive, Vol. 2016 (2016).
[38]
Raluca Ada Popa, Frank H. Li, and Nickolai Zeldovich. 2013. An Ideal-Security Protocol for Order-Preserving Encoding. In SP '13. IEEE Computer Society, Washington, DC, USA, 463--477.
[39]
Raluca Ada Popa, Catherine M. S. Redfield, Nickolai Zeldovich, and Hari Balakrishnan. 2011. CryptDB: Protecting Confidentiality with Encrypted Query Processing. In SOSP '11. ACM, New York, NY, USA, 85--100.
[40]
Pille Pullonen, Dan Bogdanov, and Thomas Schneider. 2012. The design and implementation of a two-party protocol suite for SHAREMIND 3. Technical Report. CYBERNETICA Institute of Information Security.
[41]
Daniel S. Roche, Daniel Apon, Seung Geol Choi, and Arkady Yerukhimovich. 2016. POPE: Partial Order Preserving Encoding. In CCS '16. 1131--1142.
[42]
Fabian Taigel, Anselme K. Tueno, and Richard Pibernik. 2018. Privacy-preserving condition-based forecasting using machine learning. Journal of Business Economics (05 Jan 2018).
[43]
Isamu Teranishi, Moti Yung, and Tal Malkin. 2014. Order-preserving encryption secure beyond one-wayness. In ASIACRYPT '14 .
[44]
Anselme Tueno, Yordan Boev, and Florian Kerschbaum. 2019 a. Non-Interactive Private Decision Tree Evaluation. CoRR, Vol. abs/1909.08362 (2019).
[45]
Anselme Tueno, Florian Kerschbaum, and Stefan Katzenbeisser. 2019 b. Private Evaluation of Decision Trees using Sublinear Cost. PoPETs, Vol. 2019, 1 (2019), 266--286. https://doi.org/10.2478/popets-2019-0015
[46]
Anselme Tueno, Florian Kerschbaum, Stefan Katzenbeisser, Yordan Boev, and Mubashir Qureshi. 2020. Secure Computation of the kth-Ranked Element in a Star Network. In Financial Cryptography and Data Security (FC).
[47]
Andrew C. Yao. 1982. Protocols for Secure Computations. In SFCS '82. IEEE Computer Society, Washington, DC, USA, 160--164.
[48]
Samee Zahur, Mike Rosulek, and David Evans. 2015. Two Halves Make a Whole - Reducing Data Transfer in Garbled Circuits Using Half Gates (EUROCRYPT'15).

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  • (2024)Towards Practical Multi-Client Order-Revealing Encryption: Improvement and ApplicationIEEE Transactions on Dependable and Secure Computing10.1109/TDSC.2023.326865221:3(1111-1126)Online publication date: May-2024
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  • (2023)Conjunctive Searchable Symmetric Encryption from Hard Lattices2023 IEEE 8th European Symposium on Security and Privacy (EuroS&P)10.1109/EuroSP57164.2023.00061(958-978)Online publication date: Jul-2023
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cover image ACM Conferences
ASIA CCS '20: Proceedings of the 15th ACM Asia Conference on Computer and Communications Security
October 2020
957 pages
ISBN:9781450367509
DOI:10.1145/3320269
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Published: 05 October 2020

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  1. multiparty computation
  2. order-preserving encryption

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  • (2024)Confidential Inference in Decision TreesVLSI-SoC 2023: Innovations for Trustworthy Artificial Intelligence10.1007/978-3-031-70947-0_14(273-297)Online publication date: 29-Dec-2024
  • (2023)Conjunctive Searchable Symmetric Encryption from Hard Lattices2023 IEEE 8th European Symposium on Security and Privacy (EuroS&P)10.1109/EuroSP57164.2023.00061(958-978)Online publication date: Jul-2023
  • (2023)Securing Decision Tree Inference Using Order-Preserving Cryptography2023 IEEE 5th International Conference on Artificial Intelligence Circuits and Systems (AICAS)10.1109/AICAS57966.2023.10168588(1-5)Online publication date: 11-Jun-2023
  • (2023)A Secure Order-Preserving Encryption Scheme Based on Encrypted IndexWeb and Big Data10.1007/978-3-031-25201-3_19(247-261)Online publication date: 10-Feb-2023
  • (2022)Efficient Encrypted Range Query on Cloud PlatformsACM Transactions on Cyber-Physical Systems10.1145/35486576:3(1-23)Online publication date: 19-Jul-2022
  • (2022)BlockOPE: Efficient Order-Preserving Encryption for Permissioned Blockchain2022 IEEE 38th International Conference on Data Engineering (ICDE)10.1109/ICDE53745.2022.00098(1245-1258)Online publication date: May-2022
  • (2022)A Crypto-Assisted Approach for Publishing Graph Statistics with Node Local Differential Privacy2022 IEEE International Conference on Big Data (Big Data)10.1109/BigData55660.2022.10020435(5765-5774)Online publication date: 17-Dec-2022
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  • (2021)Efficient All-or-Nothing Public Key Encryption With Authenticated Equality TestIEEE Access10.1109/ACCESS.2021.30929459(94099-94108)Online publication date: 2021

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