Data‐Class‐Specific All‐Optical Transformations and Encryption

Author:

Bai Bijie12ORCID,Wei Heming3,Yang Xilin12,Gan Tianyi14,Mengu Deniz12,Jarrahi Mona14,Ozcan Aydogan124ORCID

Affiliation:

1. Electrical and Computer Engineering Department University of California, Los Angeles Los Angeles CA 90095 USA

2. Bioengineering Department University of California, Los Angeles Los Angeles CA 90095 USA

3. Key Laboratory of Specialty Fiber Optics and Optical Access Networks Joint International Research Laboratory of Specialty Fiber Optics and Advanced Communication Shanghai University Shanghai 200444 China

4. California NanoSystems Institute (CNSI) University of California, Los Angeles Los Angeles CA 90095 USA

Abstract

AbstractDiffractive optical networks provide rich opportunities for visual computing tasks. Here, data‐class‐specific transformations that are all‐optically performed between the input and output fields‐of‐view (FOVs) of a diffractive network are presented. The visual information of the objects is encoded into the amplitude (A), phase (P), or intensity (I) of the optical field at the input, which is all‐optically processed by a data‐class‐specific diffractive network. At the output, an image sensor‐array directly measures the transformed patterns, all‐optically encrypted using the transformation matrices preassigned to different data classes, i.e., a separate matrix for each data class. The original input images can be recovered by applying the correct decryption key (the inverse transformation) corresponding to the matching data class, while applying any other key will lead to loss of information. All‐optical class‐specific transformations covering AA, II, and PI transformations using various image datasets are numerically demonstrated. The feasibility of this framework is also experimentally validated by fabricating class‐specific II transformation diffractive networks and is successfully tested at different parts of the electromagnetic spectrum, i.e., 1550 nm and 0.75 mm wavelengths. Data‐class‐specific all‐optical transformations provide a fast and energy‐efficient method for image and data encryption, enhancing data security and privacy.

Publisher

Wiley

Subject

Mechanical Engineering,Mechanics of Materials,General Materials Science

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