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Verifiable Privacy-Preserving Computing (2309.08248v3)

Published 15 Sep 2023 in cs.CR

Abstract: Privacy-preserving computation (PPC) methods, such as secure multiparty computation (MPC) and homomorphic encryption (HE), are deployed increasingly often to guarantee data confidentiality in computations over private, distributed data. Similarly, we observe a steep increase in the adoption of zero-knowledge proofs (ZKPs) to guarantee (public) verifiability of locally executed computations. We project that applications that are data intensive and require strong privacy guarantees, are also likely to require verifiable correctness guarantees, especially when outsourced. While the combination of methods for verifiability and privacy protection has clear benefits, certain challenges stand before their widespread practical adoption. In this work, we analyze existing solutions that combine verifiability with privacy-preserving computations over distributed data, in order to preserve confidentiality and guarantee correctness at the same time. We classify and compare 37 different schemes, regarding solution approach, security, efficiency, and practicality. Lastly, we discuss some of the most promising solutions in this regard, and present various open challenges and directions for future research.

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References (86)
  1. Blockchain for Genomics and Healthcare: A Literature Review, Current Status, Classification and Open Issues. PeerJ 9 (2021), e12130. https://doi.org/10.7717/peerj.12130
  2. Blockchain-Based Identity Management System and Self-Sovereign Identity Ecosystem: A Comprehensive Survey. IEEE Access 10 (2022), 113436–113481. https://doi.org/10.1109/ACCESS.2022.3216643
  3. Blockchain for Genomics: A Systematic Literature Review. Distributed Ledger Technologies: Research and Practice 1, 2 (Dec. 2022), 11:1–11:28. https://doi.org/10.1145/3563044
  4. Ramiro Alvarez and Mehrdad Nojoumian. 2020. Comprehensive Survey on Privacy-Preserving Protocols for Sealed-Bid Auctions. Computers & Security 88 (Jan. 2020), 101502. https://doi.org/10.1016/j.cose.2019.03.023
  5. AMD. 2023. AMD Secure Encrypted Virtualization. https://www.amd.com/en/processors/amd-secure-encrypted-virtualization
  6. A Guide to Fully Homomorphic Encryption. https://eprint.iacr.org/2015/1192
  7. Multiparty Computation with Low Communication, Computation and Interaction via Threshold FHE. In Advances in Cryptology – EUROCRYPT 2012 (Lecture Notes in Computer Science), David Pointcheval and Thomas Johansson (Eds.). Springer, Berlin, Heidelberg, 483–501. https://doi.org/10.1007/978-3-642-29011-4_29
  8. Gilad Asharov and Claudio Orlandi. 2012. Calling Out Cheaters: Covert Security with Public Verifiability. In Advances in Cryptology – ASIACRYPT 2012 (Lecture Notes in Computer Science), Xiaoyun Wang and Kazue Sako (Eds.). Springer, Berlin, Heidelberg, 681–698. https://doi.org/10.1007/978-3-642-34961-4_41
  9. Thomas Attema and Ronald Cramer. 2020. Compressed ΣΣ\Sigmaroman_Σ-Protocol Theory and Practical Application to Plug & Play Secure Algorithmics. In Advances in Cryptology – CRYPTO 2020 (Lecture Notes in Computer Science), Daniele Micciancio and Thomas Ristenpart (Eds.). Springer International Publishing, Cham, 513–543. https://doi.org/10.1007/978-3-030-56877-1_18
  10. Abinaya B. and Santhi S. 2021. A Survey on Genomic Data by Privacy-Preserving Techniques Perspective. Computational Biology and Chemistry 93 (Aug. 2021), 107538. https://doi.org/10.1016/j.compbiolchem.2021.107538
  11. Crowd Verifiable Zero-Knowledge and End-to-End Verifiable Multiparty Computation. In Advances in Cryptology – ASIACRYPT 2020 (Lecture Notes in Computer Science), Shiho Moriai and Huaxiong Wang (Eds.). Springer International Publishing, Cham, 717–748. https://doi.org/10.1007/978-3-030-64840-4_24
  12. Reusable Two-Round MPC from DDH. In Theory of Cryptography (Lecture Notes in Computer Science), Rafael Pass and Krzysztof Pietrzak (Eds.). Springer International Publishing, Cham, 320–348. https://doi.org/10.1007/978-3-030-64378-2_12
  13. SoK: Privacy-Enhancing Technologies in Finance. https://eprint.iacr.org/2023/122
  14. Publicly Auditable Secure Multi-Party Computation. In Security and Cryptography for Networks (Lecture Notes in Computer Science), Michel Abdalla and Roberto De Prisco (Eds.). Springer International Publishing, Cham, 175–196. https://doi.org/10.1007/978-3-319-10879-7_11
  15. Efficient Constant-Round MPC with Identifiable Abort and Public Verifiability. In Advances in Cryptology – CRYPTO 2020 (Lecture Notes in Computer Science), Daniele Micciancio and Thomas Ristenpart (Eds.). Springer International Publishing, Cham, 562–592. https://doi.org/10.1007/978-3-030-56880-1_20
  16. Donald Beaver. 1992. Efficient Multiparty Protocols Using Circuit Randomization. In Advances in Cryptology — CRYPTO ’91 (Lecture Notes in Computer Science), Joan Feigenbaum (Ed.). Springer, Berlin, Heidelberg, 420–432. https://doi.org/10.1007/3-540-46766-1_34
  17. The Round Complexity of Secure Protocols. In Proceedings of the Twenty-Second Annual ACM Symposium on Theory of Computing (STOC ’90). Association for Computing Machinery, New York, NY, USA, 503–513. https://doi.org/10.1145/100216.100287
  18. Zerocash: Decentralized Anonymous Payments from Bitcoin. https://eprint.iacr.org/2014/349
  19. Privacy-Preserving Solutions for Blockchain: Review and Challenges. IEEE Access 7 (2019), 164908–164940. https://doi.org/10.1109/ACCESS.2019.2950872
  20. Daniel J Bernstein. 2002. Pippenger’s Exponentiation Algorithm. (Jan. 2002). https://cr.yp.to/papers/pippenger-20020118-retypeset20220327.pdf Unpublished manuscript.
  21. Flexible and Efficient Verifiable Computation on Encrypted Data. https://eprint.iacr.org/2020/1526
  22. Balancing Privacy and Accountability in Digital Payment Methods Using zk-SNARKs. In 2022 19th Annual International Conference on Privacy, Security & Trust (PST). IEEE, Fredericton, NB, Canada, 1–10. https://doi.org/10.1109/PST55820.2022.9851987
  23. ZEXE: Enabling Decentralized Private Computation. In 2020 IEEE Symposium on Security and Privacy (SP). IEEE, San Francisco, CA, USA, 947–964. https://doi.org/10.1109/SP40000.2020.00050
  24. Zether: Towards Privacy in a Smart Contract World. In Financial Cryptography and Data Security (Lecture Notes in Computer Science), Joseph Bonneau and Nadia Heninger (Eds.). Springer International Publishing, Cham, 423–443. https://doi.org/10.1007/978-3-030-51280-4_23
  25. Bulletproofs: Short Proofs for Confidential Transactions and More. In 2018 IEEE Symposium on Security and Privacy (SP). IEEE, San Francisco, CA, USA, 315–334. https://doi.org/10.1109/SP.2018.00020
  26. Dario Catalano and Dario Fiore. 2013. Practical Homomorphic MACs for Arithmetic Circuits. In Advances in Cryptology – EUROCRYPT 2013 (Lecture Notes in Computer Science), Thomas Johansson and Phong Q. Nguyen (Eds.). Springer, Berlin, Heidelberg, 336–352. https://doi.org/10.1007/978-3-642-38348-9_21
  27. Verifiable Encodings for Secure Homomorphic Analytics. https://doi.org/10.48550/arXiv.2207.14071 arXiv:2207.14071 [cs]
  28. Ekiden: A Platform for Confidentiality-Preserving, Trustworthy, and Performant Smart Contracts. In 2019 IEEE European Symposium on Security and Privacy (EuroS&P). IEEE, Stockholm, Sweden, 185–200. https://doi.org/10.1109/EuroSP.2019.00023
  29. Marlin: Preprocessing zkSNARKs with Universal and Updatable SRS. In Advances in Cryptology – EUROCRYPT 2020 (Lecture Notes in Computer Science), Anne Canteaut and Yuval Ishai (Eds.). Springer International Publishing, Cham, 738–768. https://doi.org/10.1007/978-3-030-45721-1_26
  30. Fractal: Post-quantum and Transparent Recursive Proofs from Holography. In Advances in Cryptology – EUROCRYPT 2020 (Lecture Notes in Computer Science), Anne Canteaut and Yuval Ishai (Eds.). Springer International Publishing, Cham, 769–793. https://doi.org/10.1007/978-3-030-45721-1_27
  31. Information Technology Laboratory Computer Security Division. 2017. Post-Quantum Cryptography. https://csrc.nist.gov/projects/post-quantum-cryptography
  32. Multiparty Computation from Threshold Homomorphic Encryption. In Advances in Cryptology — EUROCRYPT 2001 (Lecture Notes in Computer Science), Birgit Pfitzmann (Ed.). Springer, Berlin, Heidelberg, 280–300. https://doi.org/10.1007/3-540-44987-6_18
  33. Catching MPC Cheaters: Identification and Openability. https://eprint.iacr.org/2016/611
  34. Édouard Cuvelier and Olivier Pereira. 2016. Verifiable Multi-party Computation with Perfectly Private Audit Trail. In Applied Cryptography and Network Security (Lecture Notes in Computer Science), Mark Manulis, Ahmad-Reza Sadeghi, and Steve Schneider (Eds.). Springer International Publishing, Cham, 367–385. https://doi.org/10.1007/978-3-319-39555-5_20
  35. On Secure Two-Party Integer Division. In Financial Cryptography and Data Security (Lecture Notes in Computer Science), Angelos D. Keromytis (Ed.). Springer, Berlin, Heidelberg, 164–178. https://doi.org/10.1007/978-3-642-32946-3_13
  36. Multiparty Computation from Somewhat Homomorphic Encryption. In Advances in Cryptology – CRYPTO 2012 (Lecture Notes in Computer Science), Reihaneh Safavi-Naini and Ran Canetti (Eds.). Springer, Berlin, Heidelberg, 643–662. https://doi.org/10.1007/978-3-642-32009-5_38
  37. ABY - A Framework for Efficient Mixed-Protocol Secure Two-Party Computation. In Proceedings 2015 Network and Distributed System Security Symposium. Internet Society, San Diego, CA, 1–15. https://doi.org/10.14722/ndss.2015.23113
  38. Compute, but Verify: Efficient Multiparty Computation over Authenticated Inputs. https://eprint.iacr.org/2022/1648
  39. Enarx. 2023. Enarx — Confidential Computing with WebAssembly. https://enarx.dev/
  40. Amos Fiat and Adi Shamir. 1987. How To Prove Yourself: Practical Solutions to Identification and Signature Problems. In Advances in Cryptology — CRYPTO’ 86 (Lecture Notes in Computer Science), Andrew M. Odlyzko (Ed.). Springer, Berlin, Heidelberg, 186–194. https://doi.org/10.1007/3-540-47721-7_12
  41. Efficiently Verifiable Computation on Encrypted Data. In Proceedings of the 2014 ACM SIGSAC Conference on Computer and Communications Security (CCS ’14). Association for Computing Machinery, New York, NY, USA, 844–855. https://doi.org/10.1145/2660267.2660366
  42. Boosting Verifiable Computation on Encrypted Data. In Public-Key Cryptography – PKC 2020 (Lecture Notes in Computer Science), Aggelos Kiayias, Markulf Kohlweiss, Petros Wallden, and Vassilis Zikas (Eds.). Springer International Publishing, Cham, 124–154. https://doi.org/10.1007/978-3-030-45388-6_5
  43. Rinocchio: SNARKs for Ring Arithmetic. https://eprint.iacr.org/2021/322
  44. Non-Interactive Verifiable Computing: Outsourcing Computation to Untrusted Workers. In Advances in Cryptology – CRYPTO 2010 (Lecture Notes in Computer Science), Tal Rabin (Ed.). Springer, Berlin, Heidelberg, 465–482. https://doi.org/10.1007/978-3-642-14623-7_25
  45. Rosario Gennaro and Daniel Wichs. 2013. Fully Homomorphic Message Authenticators. In Advances in Cryptology - ASIACRYPT 2013 (Lecture Notes in Computer Science), Kazue Sako and Palash Sarkar (Eds.). Springer, Berlin, Heidelberg, 301–320. https://doi.org/10.1007/978-3-642-42045-0_16
  46. Craig Gentry. 2009. Fully Homomorphic Encryption Using Ideal Lattices. In Proceedings of the Forty-First Annual ACM Symposium on Theory of Computing (STOC ’09). Association for Computing Machinery, New York, NY, USA, 169–178. https://doi.org/10.1145/1536414.1536440
  47. The Knowledge Complexity of Interactive Proof Systems. SIAM J. Comput. 18, 1 (Feb. 1989), 186–208. https://doi.org/10.1137/0218012
  48. Jens Groth. 2016. On the Size of Pairing-Based Non-interactive Arguments. In Advances in Cryptology – EUROCRYPT 2016 (Lecture Notes in Computer Science), Marc Fischlin and Jean-Sébastien Coron (Eds.). Springer, Berlin, Heidelberg, 305–326. https://doi.org/10.1007/978-3-662-49896-5_11
  49. CRGC – A Practical Framework for Constructing Reusable Garbled Circuits. https://doi.org/10.48550/arXiv.2203.12646 arXiv:2203.12646 [cs]
  50. Intel. 2023. Intel® Software Guard Extensions (Intel® SGX). https://www.intel.com/content/www/us/en/architecture-and-technology/software-guard-extensions.html
  51. Extending Oblivious Transfers Efficiently. In Advances in Cryptology - CRYPTO 2003 (Lecture Notes in Computer Science), Dan Boneh (Ed.). Springer, Berlin, Heidelberg, 145–161. https://doi.org/10.1007/978-3-540-45146-4_9
  52. Threshold Fully Homomorphic Encryption. https://eprint.iacr.org/2017/257
  53. A Framework for Outsourcing of Secure Computation. In Proceedings of the 6th Edition of the ACM Workshop on Cloud Computing Security (CCSW ’14). Association for Computing Machinery, New York, NY, USA, 81–92. https://doi.org/10.1145/2664168.2664170
  54. Transitioning Organizations to Post-Quantum Cryptography. Nature 605, 7909 (May 2022), 237–243. https://doi.org/10.1038/s41586-022-04623-2
  55. Publicly Auditable MPC-as-a-Service with Succinct Verification and Universal Setup. In 2021 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW). IEEE, Vienna, Austria, 386–411. https://doi.org/10.1109/EuroSPW54576.2021.00048
  56. Marcel Keller. 2020. MP-SPDZ: A Versatile Framework for Multi-Party Computation. https://eprint.iacr.org/2020/521
  57. MASCOT: Faster Malicious Arithmetic Secure Computation with Oblivious Transfer. In Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security (CCS ’16). Association for Computing Machinery, New York, NY, USA, 830–842. https://doi.org/10.1145/2976749.2978357
  58. Hawk: The Blockchain Model of Cryptography and Privacy-Preserving Smart Contracts. In 2016 IEEE Symposium on Security and Privacy (SP). IEEE, San Jose, CA, USA, 839–858. https://doi.org/10.1109/SP.2016.55
  59. SAVER: SNARK-friendly, Additively-homomorphic, and Verifiable Encryption and Decryption with Rerandomization. https://eprint.iacr.org/2019/1270
  60. Privacy-Preserving Homomorphic MACs with Efficient Verification. In Web Services – ICWS 2018 (Lecture Notes in Computer Science), Hai Jin, Qingyang Wang, and Liang-Jie Zhang (Eds.). Springer International Publishing, Cham, 100–115. https://doi.org/10.1007/978-3-319-94289-6_7
  61. Yehuda Lindell. 2020. Secure Multiparty Computation (MPC). https://eprint.iacr.org/2020/300
  62. vFHE: Verifiable Fully Homomorphic Encryption with Blind Hash. https://doi.org/10.48550/arXiv.2303.08886 arXiv:2303.08886 [cs]
  63. Payman Mohassel and Peter Rindal. 2018. ABY3: A Mixed Protocol Framework for Machine Learning. In Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security (CCS ’18). Association for Computing Machinery, New York, NY, USA, 35–52. https://doi.org/10.1145/3243734.3243760
  64. A Survey on the (in)Security of Trusted Execution Environments. Computers & Security 129 (June 2023), 103180. https://doi.org/10.1016/j.cose.2023.103180
  65. Satoshi Nakamoto. 2008. Bitcoin: A Peer-to-Peer Electronic Cash System. (2008). https://bitcoin.org/bitcoin.pdf Unpublished manuscript.
  66. CHEX-MIX: Combining Homomorphic Encryption with Trusted Execution Environments for Two-party Oblivious Inference in the Cloud. https://eprint.iacr.org/2021/1603
  67. Alex Ozdemir and Dan Boneh. 2022. Experimenting with Collaborative zk-SNARKs: Zero-Knowledge Proofs for Distributed Secrets. In 31st USENIX Security Symposium (USENIX Security 22). USENIX Association, Boston, MA, 4291–4308. https://www.usenix.org/conference/usenixsecurity22/presentation/ozdemir
  68. Somnath Panja and Bimal Roy. 2021. A Secure End-to-End Verifiable e-Voting System Using Blockchain and Cloud Server. Journal of Information Security and Applications 59 (June 2021), 102815. https://doi.org/10.1016/j.jisa.2021.102815
  69. Pinocchio: Nearly Practical Verifiable Computation. In 2013 IEEE Symposium on Security and Privacy. IEEE, Berkeley, CA, USA, 238–252. https://doi.org/10.1109/SP.2013.47
  70. PRIViLEDGE project. 2021. Revision of Extended Core Protocols. Public Deliverable D3.3. HORIZON 2020. https://media.voog.com/0000/0042/1115/files/D3.3%20-%20Revision%20of%20Extended%20Core%20Protocols.pdf
  71. Universally Verifiable MPC and IRV Ballot Counting. In Financial Cryptography and Data Security (Lecture Notes in Computer Science), Ian Goldberg and Tyler Moore (Eds.). Springer International Publishing, Cham, 301–319. https://doi.org/10.1007/978-3-030-32101-7_19
  72. Publicly Accountable Robust Multi-Party Computation. https://eprint.iacr.org/2022/436
  73. Function-Dependent Commitments for Verifiable Multi-party Computation. In Information Security (Lecture Notes in Computer Science), Liqun Chen, Mark Manulis, and Steve Schneider (Eds.). Springer International Publishing, Cham, 289–307. https://doi.org/10.1007/978-3-319-99136-8_16
  74. C. P. Schnorr. 1990. Efficient Identification and Signatures for Smart Cards. In Advances in Cryptology — CRYPTO’ 89 Proceedings (Lecture Notes in Computer Science), Gilles Brassard (Ed.). Springer, New York, NY, 239–252. https://doi.org/10.1007/0-387-34805-0_22
  75. Berry Schoenmakers and Meilof Veeningen. 2015. Universally Verifiable Multiparty Computation from Threshold Homomorphic Cryptosystems. In Applied Cryptography and Network Security (Lecture Notes in Computer Science), Tal Malkin, Vladimir Kolesnikov, Allison Bishop Lewko, and Michalis Polychronakis (Eds.). Springer International Publishing, Cham, 3–22. https://doi.org/10.1007/978-3-319-28166-7_1
  76. Trinocchio: Privacy-Preserving Outsourcing by Distributed Verifiable Computation. In Applied Cryptography and Network Security (Lecture Notes in Computer Science), Mark Manulis, Ahmad-Reza Sadeghi, and Steve Schneider (Eds.). Springer International Publishing, Cham, 346–366. https://doi.org/10.1007/978-3-319-39555-5_19
  77. Adi Shamir. 1979. How to Share a Secret. Commun. ACM 22, 11 (Nov. 1979), 612–613. https://doi.org/10.1145/359168.359176
  78. Gabriele Spini and Serge Fehr. 2016. Cheater Detection in SPDZ Multiparty Computation. In Information Theoretic Security (Lecture Notes in Computer Science), Anderson C.A. Nascimento and Paulo Barreto (Eds.). Springer International Publishing, Cham, 151–176. https://doi.org/10.1007/978-3-319-49175-2_8
  79. Justin Thaler. 2022. Proofs, Arguments, and Zero-Knowledge. Foundations and Trends® in Privacy and Security 4, 2–4 (Dec. 2022), 117–660. https://doi.org/10.1561/3300000030
  80. Meilof Veeningen. 2017. Pinocchio-Based Adaptive zk-SNARKs and Secure/Correct Adaptive Function Evaluation. In Progress in Cryptology - AFRICACRYPT 2017 (Lecture Notes in Computer Science), Marc Joye and Abderrahmane Nitaj (Eds.). Springer International Publishing, Cham, 21–39. https://doi.org/10.1007/978-3-319-57339-7_2
  81. Thijs Veugen. 2018. Correction to ”Improving the DGK Comparison Protocol”. https://eprint.iacr.org/2018/1100
  82. Verifiable Fully Homomorphic Encryption. https://doi.org/10.48550/arXiv.2301.07041 arXiv:2301.07041 [cs]
  83. Gavin Wood. 2014. Ethereum: A Secure Decentralised Generalised Transaction Ledger. (2014). https://gavwood.com/paper.pdf Unpublished manuscript.
  84. Andrew Chi-Chih Yao. 1986. How to Generate and Exchange Secrets. In 27th Annual Symposium on Foundations of Computer Science (Sfcs 1986). IEEE, Toronto, ON, Canada, 162–167. https://doi.org/10.1109/SFCS.1986.25
  85. Zama. 2023. Zama - Fully Homomorphic Encryption. https://www.zama.ai/
  86. ZKProof. 2022. ZKProof Wiki of Concrete ZKP Schemes. https://docs.zkproof.org/schemes
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