Security authentication using phase-encoded nanoparticle structures and polarized light

Carnicer, Artur; Hassanfiroozi, Amir; Carmona, Pedro; Huang, Yi‐Pai; Javidi, Bahram

doi:10.1364/ol.40.000135

Cited by 54 publications

(28 citation statements)

References 21 publications

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“…In practical applications, random phase masks attached to the image to be secured make the information inaccessible once the light interacting with the sample is propagated. These devices display a distinctive behavior under polarized light and consequently, the use of illuminating sources with different polarizations increase the degrees of freedom of the cryptosystem resulting in gadget which is more complex and difficult to attack [5][6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Validation of optical codes based on 3D nanostructures

Carnicer¹,

Javidi²

2017

SPIE Proceedings

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Image information encoding using random phase masks produce speckle-like noise distributions when the sample is propagated in the Fresnel domain. As a result, information cannot be accessed by simple visual inspection. Phase masks can be easily implemented in practice by attaching cello-tape to the plain-text message. Conventional 2D-phase masks can be generalized to 3D by combining glass and diffusers resulting in a more complex, physical unclonable function. In this communication, we model the behavior of a 3D phase mask using a simple approach: light is propagated trough glass using the angular spectrum of plane waves whereas the diffusor is described as a random phase mask and a blurring effect on the amplitude of the propagated wave. Using different designs for the 3D phase mask and multiple samples, we demonstrate that classification is possible using the k-nearest neighbors and random forests machine learning algorithms.

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Section: Introductionmentioning

confidence: 99%

Validation of optical codes based on 3D nanostructures

Carnicer¹,

Javidi²

2017

SPIE Proceedings

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“…This area of research includes image encryption [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15], authentication [16][17][18][19][20][21][22][23][24], and compression or secure storage [25,26]. Authenticating sensitive information is critical to discovering tampering caused by a miscreant.…”

Section: Introductionmentioning

confidence: 99%

“…Authenticating sensitive information is critical to discovering tampering caused by a miscreant. Methodologies for image authentication includes both optical [16][17][18][19][20][21] and simulated [22,23] authentication schemes.…”

Section: Introductionmentioning

confidence: 99%

“…Recently, authentication schemes have been investigated using optically tagged security codes [19][20][21]. In these authentication schemes, an object is optically tagged using a phase mask.…”

Section: Introductionmentioning

confidence: 99%

“…These structures generate distinctive polarimetric information that can be utilized to authenticate the message encoded. In [21], more complex phase masks consisted of embedding nanoparticle structures such as gold in an object. An optical set up was then used to authenticate objects containing the phase mask by illuminating the object with a laser diode.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Security authentication with a three-dimensional optical phase code using random forest classifier

2016

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An object with a unique three-dimensional (3D) optical phase mask attached is analyzed for security and authentication. These 3D optical phase masks are more difficult to duplicate or to have a mathematical formulation compared with 2D masks, and thus have improved security capabilities. A quick response code was modulated using a random 3D optical phase mask generating a 3D optical phase code (OPC). Due to the scattering of light through the 3D OPC, a unique speckle pattern based on the materials and structure in the 3D optical phase mask is generated and recorded on a CCD device. Feature extraction is performed by calculating the mean, variance, skewness, kurtosis, and entropy for each recorded speckle pattern. The random forest classifier is used for authentication. Optical experiments demonstrate the feasibility of the authentication scheme.

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Optical double-image cryptosystem based on phase truncation in the Fresnel domain

Luan

Quan

2023

Appl. Phys. B

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Security authentication using phase-encoded nanoparticle structures and polarized light

Cited by 54 publications

References 21 publications

Validation of optical codes based on 3D nanostructures

Validation of optical codes based on 3D nanostructures

Security authentication with a three-dimensional optical phase code using random forest classifier

Optical double-image cryptosystem based on phase truncation in the Fresnel domain

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