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Public-Key Encryption, Local Pseudorandom Generators, and the Low-Degree Method

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Theory of Cryptography (TCC 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14369))

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Abstract

The low-degree method postulates that no efficient algorithm outperforms low-degree polynomials in certain hypothesis-testing tasks. It has been used to understand computational indistinguishability in high-dimensional statistics.

We explore the use of the low-degree method in the context of cryptography. To this end, we apply it in the design and analysis of a new public-key encryption scheme whose security is based on Goldreich’s pseudorandom generator. The scheme is a combination of two proposals of Applebaum, Barak, and Wigderson, and inherits desirable features from both.

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References

  1. Applebaum, B., Bogdanov, A., Rosen, A.: A dichotomy for local small-bias generators. J. Cryptol. 29(3), 577–596 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  2. Applebaum, B., Barak, B., Wigderson, A.: Public-key cryptography from different assumptions. In: Proceedings of the Forty-Second ACM Symposium on Theory of Computing, STOC 2010, pp. 171–180. Association for Computing Machinery, New York (2010)

    Google Scholar 

  3. Applebaum, B., Lovett, S.: Algebraic attacks against random local functions and their countermeasures. SIAM J. Comput. 47(1), 52–79 (2018)

    Article  MathSciNet  MATH  Google Scholar 

  4. Brennan, M.S., Bresler, G.: Reducibility and statistical-computational gaps from secret leakage. In: Abernethy, J.D., Agarwal, S. (eds.) Conference on Learning Theory, COLT 2020, Graz, Austria, 9–12 July 2020, Virtual Event, vol. 125 of Proceedings of Machine Learning Research, pp. 648–847. PMLR (2020)

    Google Scholar 

  5. Barak, B., Hopkins, S.B., Kelner, J.A., Kothari, P.K., Moitra, A., Potechin, A.: A nearly tight sum-of-squares lower bound for the planted clique problem. SIAM J. Comput. 48(2), 687–735 (2019)

    Article  MathSciNet  MATH  Google Scholar 

  6. Berthet, Q., Rigollet, P.: Complexity theoretic lower bounds for sparse principal component detection. In: Shalev-Shwartz, S., Steinwart, I. (eds.) Proceedings of the 26th Annual Conference on Learning Theory, vol. 30 of Proceedings of Machine Learning Research, Princeton, NJ, USA, 12–14 June 2013, pp. 1046–1066. PMLR (2013)

    Google Scholar 

  7. Dwork, C., Naor, M., Reingold, O.: Immunizing encryption schemes from decryption errors. In: Cachin, C., Camenisch, J.L. (eds.) EUROCRYPT 2004. LNCS, vol. 3027, pp. 342–360. Springer, Heidelberg (2004). https://doi.org/10.1007/978-3-540-24676-3_21

    Chapter  Google Scholar 

  8. Feige, U., Kim, J.H., Ofek, E.: Witnesses for non-satisfiability of dense random 3cnf formulas. In: 2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS 2006), pp. 497–508 (2006)

    Google Scholar 

  9. Goldwasser, S., Micali, S.: Probabilistic encryption. J. Comput. Syst. Sci. 28(2), 270–299 (1984)

    Article  MathSciNet  MATH  Google Scholar 

  10. Goldreich, O.: Candidate one-way functions based on expander graphs. In: Goldreich, O. (ed.) Studies in Complexity and Cryptography. Miscellanea on the Interplay between Randomness and Computation. LNCS, vol. 6650, pp. 76–87. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-22670-0_10

    Chapter  Google Scholar 

  11. Hopkins, S.B., Kothari, P.K., Potechin, A., Raghavendra, P., Schramm, T., Steurer, D.: The power of sum-of-squares for detecting hidden structures. In: Umans, C. (ed.) 58th IEEE Annual Symposium on Foundations of Computer Science, FOCS 2017, Berkeley, CA, USA, 15–17 October 2017, pp. 720–731. IEEE Computer Society (2017)

    Google Scholar 

  12. Hoory, S., Linial, N., Wigderson, A.: Expander graphs and their applications. Bull. Am. Math. Soc. 43(04), 439–562 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  13. Hopkins, S.: Statistical Inference and the Sum of Squares Method. PhD thesis, Cornell University (2018)

    Google Scholar 

  14. Hopkins, S.B., Steurer, D.: Efficient bayesian estimation from few samples: community detection and related problems. In: Umans, C. (ed.) 58th IEEE Annual Symposium on Foundations of Computer Science, FOCS 2017, Berkeley, CA, USA, 15–17 October 2017, pp. 379–390. IEEE Computer Society (2017)

    Google Scholar 

  15. Hajek, B., Wu, Y., Xu, J.: Computational lower bounds for community detection on random graphs. In: Proceedings of The 28th Conference on Learning Theory, vol. 40 of Proceedings of Machine Learning Research, Paris, France, 03–06 July 2015, pp. 899–928. PMLR (2015)

    Google Scholar 

  16. Kunisky, D., Wein, A.S., Bandeira, A.S.: Notes on computational hardness of hypothesis testing: predictions using the low-degree likelihood ratio. In: Cerejeiras, P., Reissig, M. (eds.) ISAAC 2019, vol. 385, pp. 1–50. Springer, Cham (2022). https://doi.org/10.1007/978-3-030-97127-4_1

    Chapter  Google Scholar 

  17. Mossel, E., Shpilka, A., Trevisan, L.: On epsilon-biased generators in nc\({}^{\text{0 }}\). Random Struct. Algor. 29(1), 56–81 (2006)

    Article  MATH  Google Scholar 

  18. O’Donnell, R., Witmer, D.: Goldreich’s PRG: evidence for near-optimal polynomial stretch. In: 2014 IEEE 29th Conference on Computational Complexity (CCC), pp. 1–12 (2014)

    Google Scholar 

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Acknowledgments

We thank Caicai Chen, Yuval Ishai, and Chris Jones for their advice and feedback. Part of this work done when the first and second authors visited Bocconi University. Andrej Bogdanov is supported by an NSERC Discovery Grant and Hong Kong RGC GRF CUHK14209920. Pravesh Kothari is supported by NSF CAREER Award #2047933, Alfred P. Sloan Fellowship and a Google Research Scholar Award. Alon Rosen is supported by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (Grant agreement No. 101019547) and Cariplo CRYPTONOMEX grant.

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Correspondence to Andrej Bogdanov .

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© 2023 International Association for Cryptologic Research

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Bogdanov, A., Kothari, P.K., Rosen, A. (2023). Public-Key Encryption, Local Pseudorandom Generators, and the Low-Degree Method. In: Rothblum, G., Wee, H. (eds) Theory of Cryptography. TCC 2023. Lecture Notes in Computer Science, vol 14369. Springer, Cham. https://doi.org/10.1007/978-3-031-48615-9_10

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  • DOI: https://doi.org/10.1007/978-3-031-48615-9_10

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