Skip to main content
Log in

Quantum cryptographic property testing of multi-output Boolean functions

  • Published:
Quantum Information Processing Aims and scope Submit manuscript

Abstract

Compared with Boolean functions, multi-output Boolean functions (a.k.a. vectorial Boolean functions) are commonly used in classical cryptography. More generally, many cryptographic primitives can be treated as multi-output Boolean functions. Hence, the research on property testing of multi-output Boolean functions is meaningful for the design and cryptanalysis of symmetric cryptography. This paper mainly focuses on the cryptographic property testing of multi-output Boolean functions in the quantum world. Firstly, the generalized Deutsch–Jozsa algorithm is proposed to distinguish balanced multi-output Boolean functions from constant ones with a single query. This algorithm has a wider scope of applications with arbitrary ancillary inputs. The first generalized Bernstein–Vazirani algorithm suitable for multi-output Boolean functions is presented to recover the linear coefficients of linear functions. Then, combined with the generalized Deutsch–Jozsa algorithm, the quantum algorithm for estimating Walsh coefficients of multi-output Boolean functions is proposed with the same idea of quantum approximate counting algorithm, accompanied with an algorithm for computing the Walsh coefficient at a specified point based on quantum exact counting algorithm. Finally, with the usage of algorithms mentioned above, the cryptographic property testing of multi-output Boolean functions is studied. In order to describe the distances from having the certain properties, Euclidean distance and Manhattan distance are introduced as complements of Hamming distance. According to the definition, the first balance testing of multi-output Boolean functions is presented by testing the uniformity of images. The second algorithm exploits the relationship between balance and the Walsh coefficients at the point 0 which could be easily extended to k-order resiliency testing. We also briefly analyze the query complexities of strict avalanche criterion testing and k-order propagation criteria testing. The linearity testing algorithm for multi-output Boolean functions based on the generalized Bernstein–Vazirani algorithm can be adapted to Boolean functions achieving a further speedup. The non-junta testing algorithm is proposed with lower query complexity.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

References

  1. Shor, P.W.: Polynomial-time algorithms for prime factorization and discrete logarithms on a quantum computer. SIAM Rev. 41(2), 303–332 (1999)

    Article  ADS  MathSciNet  Google Scholar 

  2. Grover, L.K.: A fast quantum mechanical algorithm for database search. In: Proceedings of the Twenty-Eighth Annual ACM Symposium on Theory of Computing, pp. 212–219 (1996)

  3. Wang, F.: The hidden subgroup problem. https://arxiv.org/ftp/arxiv/papers/1008/1008.0010.pdf (2010). Accessed 7 Oct 2018

  4. Deutsch, D., Jozsa, R.: Rapid solution of problems by quantum computation. Proc. R. Soc. Lond. A (Math. Phys. Eng. Sci.) 439(1907), 553–558 (1992)

    Article  ADS  MathSciNet  Google Scholar 

  5. Bernstein, E., Vazirani, U.: Quantum complexity theory. SIAM J. Comput. 26(5), 1411–1473 (1993)

    Article  MathSciNet  Google Scholar 

  6. Simon, D.R.: On the power of quantum computation. SIAM J. Comput. 26(5), 1474–1483 (1997)

    Article  MathSciNet  Google Scholar 

  7. Kaplan, M., Leurent, G., Leverrier, A., Naya-Plasencia, M.: Breaking symmetric cryptosystems using quantum period finding. In: CRYPTO 2016, pp. 207–237 (2016)

    Chapter  Google Scholar 

  8. Leander, G., May, A.: Grover meets Simon-quantumly attacking the FX-construction. In: ASIACRYPT 2017, pp. 161–178 (2017)

    Chapter  Google Scholar 

  9. Deutsch, D.: Quantum theory, the Church–Turing principle and the universal quantum computer. Proc. R. Soc. Lond. A (Math. Phys. Eng. Sci.) 400(1818), 97–117 (1985)

    Article  ADS  MathSciNet  Google Scholar 

  10. Chi, D.P., Kim, J., Lee, S.: Quantum algorithm for generalized Deutsch-Jozsa problem. arXiv:quant-ph/0005059 (2000). Accessed 7 Oct 2018

  11. Cereceda, J.L.: Generalization of the Deutsch algorithm using two qudits. arXiv:quant-ph/0407253 (2004). Accessed 7 Oct 2018

  12. Fan, Y.: A generalization of the Deutsch–Jozsa algorithm to multi-valued quantum logic. In: ISMVL 2007, pp. 12–16 (2007)

  13. Høyer, P.: Conjugated operators in quantum algorithms. Phys. Rev. A 59, 3280 (1999)

    Article  ADS  MathSciNet  Google Scholar 

  14. Batty, M., Duncan, A.J., Braunstein, S.L.: Extending the promise of the Deutsch–Jozsa–Høyer algorithm for finite groups. LMS J. Comput. Math. 9, 40–63 (2006)

    Article  MathSciNet  Google Scholar 

  15. Bera, D.: A different Deutsch–Jozsa. Quantum Inf. Process. 14(6), 1777–1785 (2015)

    Article  ADS  MathSciNet  Google Scholar 

  16. Qiu, D., Zheng, S.: Characterizations of symmetrically partial Boolean functions with exact quantum query complexity. arXiv:1603.06505 (2016). Accessed 7 Oct 2018

  17. Maitra, S., Mukhopadhyay, P.: The Deutsch–Jozsa algorithm revisited in the domain of cryptographically significant Boolean functions. Int. J. Quantum Inf. 3(2), 359–370 (2005)

    Article  Google Scholar 

  18. Krishna, R., Makwana, V., Suresh, A.P.: A generalization of Bernstein–Vazirani algorithm to qudit systems. arXiv:1609.03185 (2016). Accessed 7 Oct 2018

  19. Younes, A.: A fast quantum algorithm for the affine Boolean function identification. Eur. Phys. J. Plus 130, 34 (2015)

    Article  Google Scholar 

  20. Wu, C.K., Feng, D.: Boolean Functions and their Applications in Cryptography. Springer, Heidelberg (2016)

    Book  Google Scholar 

  21. Xie, Z., Qiu, D., Cai, G.: Quantum algorithms on Walsh transform and Hamming distance for Boolean functions. Quantum Inf. Process. 17, 139 (2018)

    Article  ADS  MathSciNet  Google Scholar 

  22. Montanaro, A., de Wolf, R.: A survey of quantum property testing. Theory Comput. Libr. Grad. Surv. 7, 1–81 (2016)

    Google Scholar 

  23. Chakraborty, S., Fischer, E., Matsliah, A., de Wolf, R.: New results on quantum property testing. In: FSTTCS 2010, pp. 145–156 (2010)

  24. Bravyi, S., Harrow, A.W., Hassidim, A.: Quantum algorithms for testing properties of distributions. IEEE Trans. Inf. Theory 57(6), 3971–3981 (2011)

    Article  MathSciNet  Google Scholar 

  25. Chakraborty, K., Maitra, S.: Application of Grover’s algorithm to check non-resiliency of a Boolean function. Cryptogr. Commun. 8(3), 401–413 (2016)

    Article  MathSciNet  Google Scholar 

  26. Li, H.: A quantum algorithm for testing and learning resiliency of a Boolean function. Quantum Inf. Process. 18, 51 (2019)

    Article  ADS  MathSciNet  Google Scholar 

  27. Chakraborty, K., Chattopadhyay, A., Maitra, S.: Quantum algorithms to check Resiliency, Symmetry and Linearity of a Boolean function. https://eprint.iacr.org/2013/232.pdf (2013). Accessed 7 Oct 2018

  28. Chakraborty, K., Maitra, S.: Improved quantum test for linearity of a Boolean function. arXiv:1306.6195 (2013). Accessed 7 Oct 2018

  29. Hillery, M., Andersson, E.: Quantum tests for the linearity and permutation invariance of Boolean functions. Phys. Rev. A 84, 062329 (2011)

    Article  ADS  Google Scholar 

  30. El-Wazan, K., Younes, A., Doma, S.B.: A quantum algorithm for testing juntas in Boolean functions. arXiv:1701.02143 (2017). Accessed 7 Oct 2018

  31. El-Wazan, K., Younes, A., Doma, S.B.: A Quantum algorithm for testing junta variables and learning Boolean functions via entanglement measure. arXiv:1710.10495 (2017). Accessed 7 Oct 2018

  32. Brassard, G., Høyer, P., Mosca, M.: Quantum amplitude amplification and estimation. Quantum computation and information: a millennium volume. Contemp. Math. 305, 53–74 (2002)

    Article  Google Scholar 

  33. Huang, H.L., Goswami, A.K., Bao, W.S., Panigrahi, P.K.: Demonstration of essentiality of entanglement in a Deutsch-like quantum algorithm. Sci. China Phys. Mech. Astron. 61(6), 060311 (2018)

    Article  ADS  Google Scholar 

  34. Gangopadhyay, S., Behera, B.K., Panigrahi, P.K.: Generalization and demonstration of an entanglement-based Deutsch–Jozsa-like algorithm using a 5-qubit quantum computer. Quantum Inf. Process. 17(7), 160 (2018)

    Article  ADS  MathSciNet  Google Scholar 

  35. Nielsen, M.A., Chuang, I.L.: Quantum Computation and Quantum Information, 10th Anniversary edn. Cambridge University Press, New York (2010)

    Book  Google Scholar 

  36. Benenti, G., Casati, G., Strini, G.: Principles of Quantum Computation and Information, vol. I. World Scientific, Singapore (2007)

    Book  Google Scholar 

  37. Loceff, M.: A Course in Quantum Computing. http://lapastillaroja.net/wp-content/uploads/2016/09/Intro_to_QC_Vol_1_Loceff.pdf (2016). Accessed 5 Jan 2019

  38. Bergou, J.A., Hillery, M.: Quantum-state filtering applied to the discrimination of Boolean functions. Phys. Rev. A 72, 012302 (2005)

    Article  ADS  Google Scholar 

  39. Bergou, J.A., Herzog, U., Hillery, M.: Quantum filtering and discrimination between sets of Boolean functions. Phys. Rev. Lett. 90, 257901 (2003)

    Article  ADS  Google Scholar 

  40. Blum, M., Luby, M., Rubinfield, R.: Self-testing/correcting with applications to numerical problems. J. Comput. Syst. Sci. 47(3), 549–595 (1993)

    Article  MathSciNet  Google Scholar 

  41. Yu, C., Guo, B., Yang, S.: Measurable genuine tripartite entanglement of (\(2\otimes 2 \otimes n\))-dimensional quantum states via only two simultaneous copies. Phys. Rev. A 93, 042304 (2016)

    Article  ADS  Google Scholar 

  42. Atıcı, A., Servedio, R.A.: Quantum algorithms for learning and testing juntas. Quantum Inf. Process. 6(5), 323–348 (2007)

    Article  MathSciNet  Google Scholar 

  43. Floess, D.F., Andersson, E., Hillery, M.: Quantum algorithms for testing Boolean functions. In: Proceedings Sixth Workshop on Developments in Computational Models: Causality, Computation, and Physics, pp. 101–108 (2010)

    Article  Google Scholar 

  44. Li, H., Yang, L.: A quantum algorithm for approximating the influences of Boolean functions and its applications. Quantum Inf. Process. 14(6), 1787–1797 (2015)

    Article  ADS  MathSciNet  Google Scholar 

  45. Ambainis, A., Belovs, A., Regev, O., De Wolf, R.: Efficient quantum algorithms for (gapped) group testing and junta testing. In: Proceedings of the Twenty-Seventh Annual ACM-SIAM Symposium on Discrete Algorithms, pp. 903–922 (2016)

  46. Bera, D., Maitra, S., Tharrmashastha, S.: Quantum Algorithms for Autocorrelation Spectrum. arXiv:1808.04448 (2018). Accessed 16 Oct 2018

  47. Yoder, T.J., Low, G.H., Chuang, I.L.: Fixed-point quantum search with an optimal number of queries. Phys. Rev. Lett. 113, 210501 (2014)

    Article  ADS  Google Scholar 

  48. Younes, A., Rowe, J., Miller, J.: Enhanced quantum searching via entanglement and partial diffusion. Physica D: Nonlinear Phenom. 237(8), 1074–1078 (2008)

    Article  ADS  MathSciNet  Google Scholar 

Download references

Acknowledgements

The authors are grateful to the anonymous reviewers for their constructive comments to improve this paper.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jiansheng Guo.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Cui, J., Guo, J. Quantum cryptographic property testing of multi-output Boolean functions. Quantum Inf Process 18, 182 (2019). https://doi.org/10.1007/s11128-019-2299-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s11128-019-2299-1

Keywords

Navigation