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Deep Optical Cryptography: Joint Encryption and LC Lens Key Generation for Secure Displays.

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Title: Deep Optical Cryptography: Joint Encryption and LC Lens Key Generation for Secure Displays.
Authors: Chen, Ting‐Yu1 (AUTHOR), Wu, Jia‐Lun1 (AUTHOR), Tung, Shao‐En1 (AUTHOR), Chen, Hung‐Shan2 (AUTHOR), Hung, Yi2 (AUTHOR), Chen, Sung‐Nan2 (AUTHOR), Tien, Chung‐Hao1 (AUTHOR) chtien@nycu.edu.tw
Source: Journal of the Society for Information Display. May2026, Vol. 34 Issue 5, p517-526. 10p.
Subjects: Visual cryptography, Spatial light modulators, Display systems, Computer security, Electronic authentication, Data encryption
Abstract: We present a learning‐based visual cryptography system that performs computational encryption and distance‐separated optical decryption using a liquid crystal (LC) modulator. The model jointly learns a ciphertext image and an LC‐based optical key such that their optical transmittance modulation recovers the plaintext at a designated capture distance. Decryption succeeds only for the correctly matched ciphertext–key pair, whereas mismatched keys produce visually uninformative outputs. We further address practical misalignment by incorporating shift‐aware training and a patch encryption strategy to enhance lateral (X–Y) shift tolerance. Quantitative evaluation using YOLO‐based digit recognition metrics and MS‐SSIM demonstrates improved robustness under spatial displacement, with experimental results consistent with simulation. These results validate a device‐bound, physically realizable visual cryptography framework that is promising for secure display, authentication, and anticounterfeiting applications. [ABSTRACT FROM AUTHOR]
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Database: Engineering Source
Description
Abstract:We present a learning‐based visual cryptography system that performs computational encryption and distance‐separated optical decryption using a liquid crystal (LC) modulator. The model jointly learns a ciphertext image and an LC‐based optical key such that their optical transmittance modulation recovers the plaintext at a designated capture distance. Decryption succeeds only for the correctly matched ciphertext–key pair, whereas mismatched keys produce visually uninformative outputs. We further address practical misalignment by incorporating shift‐aware training and a patch encryption strategy to enhance lateral (X–Y) shift tolerance. Quantitative evaluation using YOLO‐based digit recognition metrics and MS‐SSIM demonstrates improved robustness under spatial displacement, with experimental results consistent with simulation. These results validate a device‐bound, physically realizable visual cryptography framework that is promising for secure display, authentication, and anticounterfeiting applications. [ABSTRACT FROM AUTHOR]
ISSN:10710922
DOI:10.1002/jsid.70075