Abstract
The Internet of Things rapid growth poses privacy and security challenges for the traditional key storage methods. Physical Unclonable Functions offer a potential solution but require secure fuzzy extractors to ensure reliable replication. This paper introduces X-Lock, a novel and secure computational fuzzy extractor that addresses the limitations faced by traditional solutions in resource-constrained IoT devices. X-Lock offers a reusable and robust solution, effectively mitigating the impacts of bias and correlation through its design. Leveraging the preferred state of a noisy source, X-Lock encrypts a random string of bits that can be later used as seed to generate multiple secret keys. To prove our claims, we provide a comprehensive theoretical analysis, addressing security considerations, and implement the proposed model. To evaluate the effectiveness and superiority of our proposal, we also provide practical experiments and compare the results with existing approaches. The experimental findings demonstrate the efficacy of our algorithm, showing comparable memory cost (\(\approx 2.4\) KB for storing 5 keys of 128 bits) while being 3 orders of magnitude faster with respect to the state-of-the-art solution (0.086 ms against 15.51 s).
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
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). https://doi.org/10.1007/978-3-319-60080-2_1
Boyen, X.: Reusable cryptographic fuzzy extractors. In: Proceedings of the 11th ACM Conference on Computer and Communications Security, pp. 82–91. Association for Computing Machinery (2004). https://doi.org/10.1145/1030083.1030096
Boyen, X., Dodis, Y., Katz, J., Ostrovsky, R., Smith, A.: Secure remote authentication using biometric data. In: 24th Annual International Conference on the Theory and Applications of Cryptographic Techniques, Aarhus, Denmark, May 22–26, 2005. Proceedings 24, pp. 147–163 (2005)
Canetti, R., Dakdouk, R.R.: Obfuscating point functions with multibit output. In: Smart, N. (ed.) EUROCRYPT 2008. LNCS, vol. 4965, pp. 489–508. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540-78967-3_28
Canetti, R., Fuller, B., Paneth, O., Reyzin, L., Smith, A.: Reusable fuzzy extractors for low-entropy distributions. In: Fischlin, M., Coron, J.S. (eds.) Advances in Cryptology - EUROCRYPT 2016, pp. 117–146. Springer, Berlin Heidelberg, Berlin, Heidelberg (2016)
Canetti, R., Fuller, B., Paneth, O., Reyzin, L., Smith, A.: Reusable fuzzy extractors for low-entropy distributions. J. Cryptol. 34, 1–33 (2021)
Chang, C.H., Zheng, Y., Zhang, L.: A retrospective and a look forward: fifteen years of physical unclonable function advancement. IEEE Circuits Syst. Mag. 17(3), 32–62 (2017)
Chen, B., Ignatenko, T., Willems, F., Maes, R., van der Sluis, E., Selimis, G.: High-rate error correction schemes for sram-pufs based on polar codes. arXiv preprint arXiv:1701.07320 (2017)
Cheon, J.H., Jeong, J., Kim, D., Lee, J.: A reusable fuzzy extractor with practical storage size: Modifying canetti et al’.s construction. In: Information Security and Privacy: 23rd Australasian Conference, ACISP 2018, Wollongong, NSW, Australia, July 11–13, 2018, Proceedings 23, pp. 28–44 (2018)
Dodis, Y., Ostrovsky, R., Reyzin, L., Smith, A.: Fuzzy extractors: how to generate strong keys from biometrics and other noisy data. SIAM J. Comput. 38(1), 97–139 (2008). https://doi.org/10.1137/060651380
Dolev, D., Yao, A.: On the security of public key protocols. IEEE Trans. Inf. Theory 29(2), 198–208 (1983)
Fuller, B., Meng, X., Reyzin, L.: Computational fuzzy extractors. In: Advances in Cryptology-ASIACRYPT 2013: 19th International Conference on the Theory and Application of Cryptology and Information Security, Bengaluru, India, December 1–5, 2013, Proceedings, Part I 19. pp. 174–193. Springer (2013)
Fuller, B., Meng, X., Reyzin, L.: Computational fuzzy extractors. Inf. Comput. 275, 104602 (2020)
Hiller, M.: Key derivation with physical unclonable functions. Ph.D. thesis, Technische Universität München (2016)
Liu, M., Zhou, C., Tang, Q., Parhi, K.K., Kim, C.H.: A data remanence based approach to generate 100% stable keys from an sram physical unclonable function. In: 2017 IEEE/ACM International Symposium on Low Power Electronics and Design (ISLPED), pp. 1–6 (2017)
Lynn, B., Prabhakaran, M., Sahai, A.: Positive results and techniques for obfuscation. In: Cachin, C., Camenisch, J.L. (eds.) EUROCRYPT 2004. LNCS, vol. 3027, pp. 20–39. Springer, Heidelberg (2004). https://doi.org/10.1007/978-3-540-24676-3_2
Maes, R., van der Leest, V., van der Sluis, E., Willems, F.: Secure key generation from biased PUFs. In: Güneysu, T., Handschuh, H. (eds.) CHES 2015. LNCS, vol. 9293, pp. 517–534. Springer, Heidelberg (2015). https://doi.org/10.1007/978-3-662-48324-4_26
Obermaier, J., Immler, V., Hiller, M., Sigl, G.: A measurement system for capacitive puf-based security enclosures. In: Proceedings of the 55th Annual Design Automation Conference, pp. 1–6 (2018)
Rahman, M.T., Hosey, A., Guo, Z., Carroll, J., Forte, D., Tehranipoor, M.: Systematic correlation and cell neighborhood analysis of sram puf for robust and unique key generation. J. Hardw. Syst. Secur. 1, 137–155 (2017)
Roel, M.: Physically unclonable functions: Constructions, properties and applications, pp. 148–160. Katholieke Universiteit Leuven, Belgium pp (2012)
Seo, M., Kim, S., Lee, D.H., Park, J.H.: Emblem:(r) lwe-based key encapsulation with a new multi-bit encoding method. Int. J. Inf. Secur. 19, 383–399 (2020)
Shafarevich, I.R., Remizov, A.O.: Linear algebra and geometry. Springer Science & Business Media (2012)
Suzuki, M., Ueno, R., Homma, N., Aoki, T.: Efficient fuzzy extractors based on ternary debiasing method for biased physically unclonable functions. IEEE Trans. Circuits Syst. I Regul. Pap. 66(2), 616–629 (2018)
Ueno, R., Suzuki, M., Homma, N.: Tackling biased pufs through biased masking: A debiasing method for efficient fuzzy extractor. IEEE Trans. Comput. 68(7), 1091–1104 (2019)
Wen, Y., Liu, S.: Reusable fuzzy extractor from lwe. In: Information Security and Privacy: 23rd Australasian Conference, ACISP 2018, Wollongong, NSW, Australia, July 11–13, 2018, Proceedings, pp. 13–27 (2018)
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). https://doi.org/10.1007/978-3-030-03332-3_17
Wilde, F., Gammel, B.M., Pehl, M.: Spatial correlation analysis on physical unclonable functions. IEEE Trans. Inf. Forensics Secur. 13(6), 1468–1480 (2018). https://doi.org/10.1109/TIFS.2018.2791341
Woo, J., Kim, J., Park, J.H.: Robust and reusable fuzzy extractors from non-uniform learning with errors problem. Comput. Mater. Continua 74(1) (2023)
Acknowledgments
This work was partially supported by project SERICS (PE00000014) under the NRRP MUR program funded by the EU - NGEU.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Liberati, E., Visintin, A., Lazzeretti, R., Conti, M., Uluagac, S. (2024). X-Lock: A Secure XOR-Based Fuzzy Extractor for Resource Constrained Devices. In: Pöpper, C., Batina, L. (eds) Applied Cryptography and Network Security. ACNS 2024. Lecture Notes in Computer Science, vol 14583. Springer, Cham. https://doi.org/10.1007/978-3-031-54770-6_8
Download citation
DOI: https://doi.org/10.1007/978-3-031-54770-6_8
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-54769-0
Online ISBN: 978-3-031-54770-6
eBook Packages: Computer ScienceComputer Science (R0)