2020
DOI: 10.1088/2040-8986/aba47f
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Multiple-image hybrid encryption based on compressive sensing and diffractive imaging

Abstract: In this paper, the Hybrid-II method for encrypting multiple images by combining simple modified diffractive imaging-based encoding (SMDIBE) and compressive sensing (CS) algorithm is developed. Separately encrypted images are combined in a single plane with the space multiplexing technique and authorization is provided for different users. The matrix size of the ciphertext is also reduced by a method that reproduces the plane containing images as amplitude and phase information. With the Hybrid-II method, a dif… Show more

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Cited by 10 publications
(3 citation statements)
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“…One of the best ways to develop a method that is robust to CPA is to make the use of the mathematical model meaningless by preventing the direct relationship between the plaintext and corresponding ciphertext. Studies have also been done to solve the vulnerability of diffractive imaging-based encryption against CPA in this way [31,79,83].…”
Section: Chosen Plaintext Attacks (Cpas)mentioning
confidence: 99%
“…One of the best ways to develop a method that is robust to CPA is to make the use of the mathematical model meaningless by preventing the direct relationship between the plaintext and corresponding ciphertext. Studies have also been done to solve the vulnerability of diffractive imaging-based encryption against CPA in this way [31,79,83].…”
Section: Chosen Plaintext Attacks (Cpas)mentioning
confidence: 99%
“…(VC) [19][20][21][22], compressive sensing [23][24][25], chaotic system [26,27], moiré-pixel matrix [28], QR code [29], metasurface [30,31], and neural network [32][33][34][35].…”
Section: Introductionmentioning
confidence: 99%
“…Reference [ 5 ] trades off the main evaluation indicators of image hiding technology between robustness and invisibility and then proposes a generalized LSB algorithm. References [ 6 , 7 , 8 ] first scramble the image and then hide different amounts of information on the three color components of R, G, and B, thereby improving the standard LSB algorithm.…”
Section: Introductionmentioning
confidence: 99%