Generic Constructions of Robustly Reusable Fuzzy Extractor

  • Yunhua Wen
  • Shengli LiuEmail author
  • Dawu Gu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11443)


Robustly reusable Fuzzy Extractor (rrFE) considers reusability and robustness simultaneously. We present two approaches to the generic construction of rrFE. Both of approaches make use of a secure sketch and universal hash functions. The first approach also employs a special pseudo-random function (PRF), namely unique-input key-shift (ui-ks) secure PRF, and the second uses a key-shift secure auxiliary-input authenticated encryption (AIAE). The ui-ks security of PRF (resp. key-shift security of AIAE), together with the homomorphic properties of secure sketch and universal hash function, guarantees the reusability and robustness of rrFE. Meanwhile, we show two instantiations of the two approaches respectively. The first instantiation results in the first rrFE from the LWE assumption, while the second instantiation results in the first rrFE from the DDH assumption over non-pairing groups.


Fuzzy extractor Reusability Robustness 



We would like to thank the reviewers for their valuable comments. Yunhua Wen and Shengli Liu are supported by the National Natural Science Foundation of China (Grant No. 61672346). Dawu Gu is sponsored by the Natural Science Foundation of China (Grant No. 61472250) and Program of Shanghai Academic Research Leader (16XD1401300).


  1. 1.
    Alamélou, Q., et al.: Pseudoentropic isometries: a new framework for fuzzy extractor reusability. In: Kim, J., Ahn, G., Kim, S., Kim, Y., López, J., Kim, T. (eds.) AsiaCCS 2018, pp. 673–684. ACM (2018).
  2. 2.
    Apon, D., Cho, C., Eldefrawy, K., Katz, J.: Efficient, reusable fuzzy extractors from LWE. In: Dolev, S., Lodha, S. (eds.) CSCML 2017. LNCS, vol. 10332, pp. 1–18. Springer, Cham (2017). Scholar
  3. 3.
    Banerjee, A., Peikert, C.: New and improved key-homomorphic pseudorandom functions. In: Garay, J.A., Gennaro, R. (eds.) CRYPTO 2014. LNCS, vol. 8616, pp. 353–370. Springer, Heidelberg (2014). Scholar
  4. 4.
    Bennett, C.H., DiVincenzo, D.P.: Quantum information and computation. Nature 404(6775), 247–255 (2000)CrossRefGoogle Scholar
  5. 5.
    Bennett, C.H., Shor, P.W.: Quantum information theory. IEEE Trans. Inf. Theory 44(6), 2724–2742 (1998). Scholar
  6. 6.
    Boyen, X.: Reusable cryptographic fuzzy extractors. In: Atluri, V., Pfitzmann, B., McDaniel, P.D. (eds.) CCS 2004, pp. 82–91. ACM (2004).
  7. 7.
    Boyen, X., Dodis, Y., Katz, J., Ostrovsky, R., Smith, A.D.: Secure remote authentication using biometric data. In: Cramer, R. (ed.) EUROCRYPT 2005. LNCS, vol. 3494, pp. 147–163. Springer, Heidelberg (2005). Scholar
  8. 8.
    Canetti, R., Fuller, B., Paneth, O., Reyzin, L., Smith, A.: Reusable fuzzy extractors for low-entropy distributions. In: Fischlin, M., Coron, J. (eds.) EUROCRYPT 2016. LNCS, vol. 9665, pp. 117–146. Springer, Heidelberg (2016). Scholar
  9. 9.
    Cramer, R., Dodis, Y., Fehr, S., Padró, C., Wichs, D.: Detection of algebraic manipulation with applications to robust secret sharing and fuzzy extractors. In: Smart, N.P. (ed.) EUROCRYPT 2008. LNCS, vol. 4965, pp. 471–488. Springer, Heidelberg (2008). Scholar
  10. 10.
    Dodis, Y., Katz, J., Reyzin, L., Smith, A.D.: Robust fuzzy extractors and authenticated key agreement from close secrets. In: Dwork, C. (ed.) CRYPTO 2006. LNCS, vol. 4117, pp. 232–250. Springer, Heidelberg (2006). Scholar
  11. 11.
    Dodis, Y., Reyzin, L., Smith, A.D.: Fuzzy extractors: how to generate strong keys from biometrics and other noisy data. In: Cachin, C., Camenisch, J. (eds.) EUROCRYPT 2004. LNCS, vol. 3027, pp. 523–540. Springer, Heidelberg (2004). Scholar
  12. 12.
    Fuller, B., Meng, X., Reyzin, L.: Computational fuzzy extractors. In: Sako, K., Sarkar, P. (eds.) ASIACRYPT 2013. LNCS, vol. 8269, pp. 174–193. Springer, Heidelberg (2013). Scholar
  13. 13.
    Galbraith, S.: New discrete logarithm records, and the death of type 1 pairings.
  14. 14.
    Han, S., Liu, S., Lyu, L.: Efficient KDM-CCA secure public-key encryption for polynomial functions. In: Cheon, J.H., Takagi, T. (eds.) ASIACRYPT 2016. LNCS, vol. 10032, pp. 307–338. Springer, Heidelberg (2016). Scholar
  15. 15.
    Hofheinz, D.: Circular chosen-ciphertext security with compact ciphertexts. In: Johansson, T., Nguyen, P.Q. (eds.) EUROCRYPT 2013. LNCS, vol. 7881, pp. 520–536. Springer, Heidelberg (2013). Scholar
  16. 16.
    Kanukurthi, B., Reyzin, L.: An improved robust fuzzy extractor. In: Ostrovsky, R., De Prisco, R., Visconti, I. (eds.) SCN 2008. LNCS, vol. 5229, pp. 156–171. Springer, Heidelberg (2008). Scholar
  17. 17.
    Kurosawa, K., Desmedt, Y.: A new paradigm of hybrid encryption scheme. In: Franklin, M. (ed.) CRYPTO 2004. LNCS, vol. 3152, pp. 426–442. Springer, Heidelberg (2004). Scholar
  18. 18.
    Lewi, K., Montgomery, H.W., Raghunathan, A.: Improved constructions of PRFs secure against related-key attacks. In: Boureanu, I., Owesarski, P., Vaudenay, S. (eds.) ACNS 2014. LNCS, vol. 8479, pp. 44–61. Springer, Cham (2014). Scholar
  19. 19.
    Li, S.Z., Jain, A.K. (eds.): Handbook of Face Recognition, 2nd edn. Springer, London (2011). Scholar
  20. 20.
    Marasco, E., Ross, A.: A survey on antispoofing schemes for fingerprint recognition systems. ACM Comput. Surv. 47(2), 28:1–28:36 (2014). Scholar
  21. 21.
    Regev, O.: On lattices, learning with errors, random linear codes, and cryptography. In: Gabow, H.N., Fagin, R. (eds.) STOC 2005, pp. 84–93. ACM (2005).
  22. 22.
    Rührmair, U., Sehnke, F., Sölter, J., Dror, G., Devadas, S., Schmidhuber, J.: Modeling attacks on physical unclonable functions. In: CCS 2010, pp. 237–249 (2010).
  23. 23.
    Suh, G.E., Devadas, S.: Physical unclonable functions for device authentication and secret key generation. In: Proceedings of the 44th Annual Design Automation Conference, pp. 9–14 (2007)Google Scholar
  24. 24.
    Wen, Y., Liu, S.: Reusable fuzzy extractor from LWE. In: Susilo, W., Yang, G. (eds.) ACISP 2018. LNCS, vol. 10946, pp. 13–27. Springer, Cham (2018). Scholar
  25. 25.
    Wen, Y., Liu, S.: Robustly reusable fuzzy extractor from standard assumptions. In: Peyrin, T., Galbraith, S. (eds.) ASIACRYPT 2018. LNCS, vol. 11274, pp. 459–489. Springer, Cham (2018). Scholar
  26. 26.
    Wen, Y., Liu, S., Gu, D.: Generic constructions of robustly reusable fuzzy extractor. Cryptology ePrint Archive, Report 2019/018 (2019).
  27. 27.
    Wen, Y., Liu, S., Han, S.: Reusable fuzzy extractor from the decisional Diffie-Hellman assumption. Des. Codes Crypt. 86(11), 2495–2512 (2018). Scholar

Copyright information

© International Association for Cryptologic Research 2019

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringShanghai Jiao Tong UniversityShanghaiChina
  2. 2.State Key Laboratory of CryptologyBeijingChina
  3. 3.Westone Cryptologic Research CenterBeijingChina

Personalised recommendations