Abstract
Sometimes fingerprint-like features are found in a material. The exciting discovery poses new challenges on how to use the features to build an object authentication protocol that could tell customers and retailers equipped with a mobile device whether a good is authentic or fake. We are exactly in this situation with Cholesteric Spherical Reflectors (CSRs), tiny spheres of liquid crystals with which we can tag or coat objects. They are being proposed as a potential game-changer material in anti-counterfeiting due to their unique optical properties. In addition to the problem of processing images and extracting the minutiæ embedded in a CSR, one major challenge is designing cryptographically secure authentication protocols. The authentication procedure has to handle unstable input data; it has to measure the distance between some reference data stored at enrollment and noisy input provided at authentication. We propose a cryptographic authentication protocol that solves the problem, and that is secure against semi-honest and malicious adversaries. We prove that our design ensures data privacy even if enrolled data are leaked and even if servers and provers are actively curious. We implement and benchmark the protocol in Python using the Microsoft SEAL library through its Python wrapper PySEAL.
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Notes
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Match and mismatch will be defined over the features metric space.
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- 3.
“Random” is intended informally, meaning “in a way that we cannot anticipate”.
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It is a means on the values of blobs, and it returns \(\bot \) when one of the elements is \(\bot \).
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Here, the number of pictures that a User takes in the enrollment and authentication can be defined by the process. We used five images in our implementation, see Sect. 5.
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Acknowledgements
We thank the reviewers for their valuable comments and suggestions. We would also like to acknowledge Prof. Dr. J. Lagerwall for providing the CSRs images. In addition, Mónica Arenas and Georgios Fotiadis would like to thank Dr. Kim Laine, from Microsoft Research, for his responsiveness and valuable comments regarding the BFV homomorphic encryption scheme and its implementation. The authors acknowledge the financial support from the Luxembourg National Research Fund (FNR) on the projects Security in the Shell “SSh” (C17/MS/11688643), No more Fakes “NoFakes” (PoC20/15299666/NOFAKES-PoC) and the CORE project Secure, Quantum-Safe, Practical Voting Technologies “EquiVox” (C19/IS/13643617/EquiVox/Ryan).
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Arenas, M.P., Bingol, M.A., Demirci, H., Fotiadis, G., Lenzini, G. (2022). A Secure Authentication Protocol for Cholesteric Spherical Reflectors Using Homomorphic Encryption. In: Batina, L., Daemen, J. (eds) Progress in Cryptology - AFRICACRYPT 2022. AFRICACRYPT 2022. Lecture Notes in Computer Science, vol 13503. Springer, Cham. https://doi.org/10.1007/978-3-031-17433-9_18
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