Papers
Topics
Authors
Recent
Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
Gemini 2.5 Flash
Gemini 2.5 Flash 63 tok/s
Gemini 2.5 Pro 49 tok/s Pro
GPT-5 Medium 11 tok/s Pro
GPT-5 High 10 tok/s Pro
GPT-4o 83 tok/s Pro
Kimi K2 139 tok/s Pro
GPT OSS 120B 438 tok/s Pro
Claude Sonnet 4 38 tok/s Pro
2000 character limit reached

Private Aggregate Queries to Untrusted Databases (2403.13296v1)

Published 20 Mar 2024 in cs.CR

Abstract: Private information retrieval (PIR), a privacy-preserving cryptographic tool, solves a simplified version of this problem by hiding the database item that a client accesses. Most PIR protocols require the client to know the exact row index of the intended database item, which cannot support the complicated aggregation-based statistical query in a similar setting. Some works in the PIR space contain keyword searching and SQL-like queries, but most need multiple interactions between the PIR client and PIR servers. Some schemes support searching SQL-like expressive queries in a single round but fail to enable aggregate queries. These schemes are the main focus of this paper. To bridge the gap, we have built a general-purpose novel information-theoretic PIR (IT-PIR) framework that permits a user to fetch the aggregated result, hiding all sensitive sections of the complex query from the hosting PIR server in a single round of interaction. In other words, the server will not know which records contribute to the aggregation. We then evaluate the feasibility of our protocol for both benchmarking and real-world application settings. For instance, in a complex aggregate query to the Twitter microblogging database of 1 million tweets, our protocol takes 0.014 seconds for a PIR server to generate the result when the user is interested in one of 3K user handles. In contrast, for a much-simplified task, not an aggregate but a positional query, Goldberg's regular IT-PIR (Oakland 2007) takes 1.13 seconds. For all possible user handles, 300K, it takes equal time compared to the regular IT-PIR. This example shows that complicated aggregate queries through our framework do not incur additional overhead if not less, compared to the conventional query.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (53)
  1. S. Winer, “Suspect accused of endangering national security in spyware theft plot,” 7 2018.
  2. S. S. Hsu, “Former acting homeland security inspector general indicted in data theft of 250,000 workers,” 3 2020.
  3. B. Chor, E. Kushilevitz, O. Goldreich, and M. Sudan, “Private information retrieval,” Journal of the ACM (JACM), vol. 45, no. 6, pp. 965–981, 1998.
  4. T. Riise, “An introduction to information-theoretic private information retrieval (it-pir),” Master’s thesis, The University of Bergen, 2019.
  5. C. Devet, I. Goldberg, and N. Heninger, “Optimally robust private information retrieval,” in 21st USENIX Security Symposium (USENIX Security 12), pp. 269–283, 2012.
  6. S. M. Hafiz and R. Henry, “A bit more than a bit is more than a bit better,” Proceedings on Privacy Enhancing Technologies, vol. 2019, no. 4, 2019.
  7. S. M. Hafiz and R. Henry, “Querying for queries: Indexes of queries for efficient and expressive it-pir,” in Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security, pp. 1361–1373, 2017.
  8. F. Wang, C. Yun, S. Goldwasser, V. Vaikuntanathan, and M. Zaharia, “Splinter: Practical private queries on public data,” in 14th USENIX Symposium on Networked Systems Design and Implementation (NSDI 17), pp. 299–313, 2017.
  9. E. Boyle, N. Gilboa, and Y. Ishai, “Function secret sharing,” in Annual international conference on the theory and applications of cryptographic techniques, pp. 337–367, Springer, 2015.
  10. Y. Zhao and H. Sun, “Information theoretic secure aggregation with user dropouts,” IEEE Transactions on Information Theory, 2022.
  11. I. Ahmad, L. Sarker, D. Agrawal, A. El Abbadi, and T. Gupta, “Coeus: A system for oblivious document ranking and retrieval,” in Proceedings of the ACM SIGOPS 28th Symposium on Operating Systems Principles, pp. 672–690, 2021.
  12. Z. Gui, K. G. Paterson, and S. Patranabis, “Rethinking searchable symmetric encryption,” Cryptology ePrint Archive, 2021.
  13. S. M. Hafiz, R. Henry, W. Wnuck, C. Gupta, and B. Vora, “smhafiz/private_queries_it_pir: Private Aggregate Queries v1.0.0 Public Release,” Dec. 2022.
  14. I. Goldberg, D. Wagner, and E. Brewer, “Privacy-enhancing technologies for the internet,” in Proceedings IEEE COMPCON 97. Digest of Papers, pp. 103–109, IEEE, 1997.
  15. H. T. Tavani and J. H. Moor, “Privacy protection, control of information, and privacy-enhancing technologies,” ACM Sigcas Computers and Society, vol. 31, no. 1, pp. 6–11, 2001.
  16. V. Seniv⁢c𝑣𝑐\mathpzc{v}{c}italic_v italic_car, B. Jerman-Blav⁢z𝑣𝑧\mathpzc{v}{z}italic_v italic_ziv⁢c𝑣𝑐\mathpzc{v}{c}italic_v italic_c, and T. Klobuv⁢c𝑣𝑐\mathpzc{v}{c}italic_v italic_car, “Privacy-enhancing technologies—approaches and development,” Computer Standards & Interfaces, vol. 25, no. 2, pp. 147–158, 2003.
  17. A. Shamir, “How to share a secret,” Communications of the ACM, vol. 22, no. 11, pp. 612–613, 1979.
  18. A. Beimel, “Secret-sharing schemes: A survey,” in International conference on coding and cryptology, pp. 11–46, Springer, 2011.
  19. R. Dingledine, N. Mathewson, and P. Syverson, “Tor: The second-generation onion router,” tech. rep., Naval Research Lab Washington DC, 2004.
  20. G. Danezis, R. Dingledine, and N. Mathewson, “Mixminion: Design of a type iii anonymous remailer protocol,” in 2003 Symposium on Security and Privacy, 2003., pp. 2–15, IEEE, 2003.
  21. P. Y. Ryan and S. A. Schneider, “Prêt à voter with re-encryption mixes,” in European Symposium on Research in Computer Security, pp. 313–326, Springer, 2006.
  22. D. Chaum, R. T. Carback, J. Clark, A. Essex, S. Popoveniuc, R. L. Rivest, P. Y. Ryan, E. Shen, A. T. Sherman, and P. L. Vora, “Scantegrity ii: End-to-end verifiability by voters of optical scan elections through confirmation codes,” IEEE transactions on information forensics and security, vol. 4, no. 4, pp. 611–627, 2009.
  23. A. Henzinger, M. M. Hong, H. Corrigan-Gibbs, S. Meiklejohn, and V. Vaikuntanathan, “One server for the price of two: Simple and fast single-server private information retrieval,” in Usenix Security, vol. 23, 2023.
  24. S. J. Menon and D. J. Wu, “Spiral: Fast, high-rate single-server pir via fhe composition,” in 2022 IEEE Symposium on Security and Privacy (SP), pp. 930–947, IEEE, 2022.
  25. T. Gong, R. Henry, A. Psomas, and A. Kate, “More is merrier in collusion mitigation,” arXiv preprint arXiv:2201.07740, 2022.
  26. Z. Wang, S.-C. S. Cheung, and Y. Luo, “Information-theoretic secure multi-party computation with collusion deterrence,” IEEE Transactions on Information Forensics and Security, vol. 12, no. 4, pp. 980–995, 2016.
  27. Z. Wang, Y. Luo, and S.-c. Cheung, “Efficient multi-party computation with collusion-deterred secret sharing,” in 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 7401–7405, IEEE, 2014.
  28. I. Goldberg, “Improving the robustness of private information retrieval,” in 2007 IEEE Symposium on Security and Privacy (SP’07), pp. 131–148, IEEE, 2007.
  29. R. Henry, Y. Huang, and I. Goldberg, “One (block) size fits all: Pir and spir with variable-length records via multi-block queries.,” in NDSS, 2013.
  30. Citeseer, 1997.
  31. R. Henry, “Polynomial batch codes for efficient it-pir,” Cryptology ePrint Archive, 2016.
  32. P. Barrett, “Implementing the rivest shamir and adleman public key encryption algorithm on a standard digital signal processor,” in Conference on the Theory and Application of Cryptographic Techniques, pp. 311–323, Springer, 1986.
  33. I. S. Duff, R. G. Grimes, and J. G. Lewis, “Sparse matrix test problems,” ACM Transactions on Mathematical Software (TOMS), vol. 15, no. 1, pp. 1–14, 1989.
  34. A. E. Johnson, T. J. Pollard, L. Shen, L.-w. H. Lehman, M. Feng, M. Ghassemi, B. Moody, P. Szolovits, L. Anthony Celi, and R. G. Mark, “Mimic-iii, a freely accessible critical care database,” Scientific data, vol. 3, no. 1, pp. 1–9, 2016.
  35. S. Kadhe, N. Rajaraman, O. O. Koyluoglu, and K. Ramchandran, “Fastsecagg: Scalable secure aggregation for privacy-preserving federated learning,” arXiv preprint arXiv:2009.11248, 2020.
  36. K. Bonawitz, V. Ivanov, B. Kreuter, A. Marcedone, H. B. McMahan, S. Patel, D. Ramage, A. Segal, and K. Seth, “Practical secure aggregation for privacy-preserving machine learning,” in proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security, pp. 1175–1191, 2017.
  37. K. Pillutla, S. M. Kakade, and Z. Harchaoui, “Robust aggregation for federated learning,” IEEE Transactions on Signal Processing, vol. 70, pp. 1142–1154, 2022.
  38. J. So, B. Güler, and A. S. Avestimehr, “Byzantine-resilient secure federated learning,” IEEE Journal on Selected Areas in Communications, vol. 39, no. 7, pp. 2168–2181, 2020.
  39. A. Bag, D. Talapatra, A. Rastogi, S. Patranabis, and D. Mukhopadhyay, “Two-in-one-sse: Fast, scalable and storage-efficient searchable symmetric encryption for conjunctive and disjunctive boolean queries,” in 23rd Privacy Enhancing Technologies Symposium (PETS 2023), 2023.
  40. T. Mayberry, E.-O. Blass, and A. H. Chan, “Efficient private file retrieval by combining oram and pir,” Cryptology ePrint Archive, 2013.
  41. E. Kushilevitz, S. Lu, and R. Ostrovsky, “On the (in) security of hash-based oblivious ram and a new balancing scheme,” in Proceedings of the twenty-third annual ACM-SIAM symposium on Discrete Algorithms, pp. 143–156, SIAM, 2012.
  42. E. Shi, T. H. H. Chan, E. Stefanov, and M. Li, “Oblivious ram with o ((log n) 3) worst-case cost,” in Advances in Cryptology–ASIACRYPT 2011: 17th International Conference on the Theory and Application of Cryptology and Information Security, Seoul, South Korea, December 4-8, 2011. Proceedings 17, pp. 197–214, Springer, 2011.
  43. E. Stefanov, M. v. Dijk, E. Shi, T.-H. H. Chan, C. Fletcher, L. Ren, X. Yu, and S. Devadas, “Path oram: an extremely simple oblivious ram protocol,” Journal of the ACM (JACM), vol. 65, no. 4, pp. 1–26, 2018.
  44. E. Stefanov and E. Shi, “Oblivistore: High performance oblivious cloud storage,” in 2013 IEEE Symposium on Security and Privacy, pp. 253–267, IEEE, 2013.
  45. E. Stefanov, E. Shi, and D. Song, “Towards practical oblivious ram,” arXiv preprint arXiv:1106.3652, 2011.
  46. Z. Wu and R. Li, “Obi: a multi-path oblivious ram for forward-and-backward-secure searchable encryption.,” in NDSS, 2023.
  47. P. Grubbs, A. Khandelwal, M.-S. Lacharité, L. Brown, L. Li, R. Agarwal, and T. Ristenpart, “Pancake: Frequency smoothing for encrypted data stores,” in 29th USENIX Security Symposium (USENIX Security 20), pp. 2451–2468, 2020.
  48. S. Maiyya, S. Vemula, D. Agrawal, A. El Abbadi, and F. Kerschbaum, “Waffle: An online oblivious datastore for protecting data access patterns,” Cryptology ePrint Archive, 2023.
  49. S. M. Hafiz, Private Information Retrieval in Practice. PhD thesis, 2021. Copyright - Database copyright ProQuest LLC; ProQuest does not claim copyright in the individual underlying works; Last updated - 2023-06-21.
  50. L. Guan, X. F. Liu, W. Sun, H. Liang, and J. J. Zhu, “Census of twitter users: Scraping and describing the national network of south korea,” Plos one, vol. 17, no. 11, p. e0277549, 2022.
  51. B. Kusumasari and N. P. A. Prabowo, “Scraping social media data for disaster communication: how the pattern of twitter users affects disasters in asia and the pacific,” Natural Hazards, vol. 103, no. 3, pp. 3415–3435, 2020.
  52. M. H. Al Walid, D. Anisuzzaman, and A. S. Saif, “Data analysis and visualization of continental cancer situation by twitter scraping,” International Journal of Modern Education and Computer Science, vol. 11, no. 7, p. 23, 2019.
  53. A. Singh, B. S. Prakash, and K. Chandrasekaran, “A comparison of linear discriminant analysis and ridge classifier on twitter data,” in 2016 International Conference on Computing, Communication and Automation (ICCCA), pp. 133–138, IEEE, 2016.

Summary

We haven't generated a summary for this paper yet.

Lightbulb On Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.