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Implementasi Secret SHAring Berbasis Visual Cryptography Menggunakan Citra Grayscale
Abstrak:
Secret sharing merupakan skema yang membagi suatu nilai secret menjadi ?? share
kemudian setiap share tersebut dibagikan kepada beberapa pihak. Setiap share
memiliki keunikan, dibutuhkan sedikitnya ?? share sebagai threshold untuk
merekontruksi secret yang asli. Secret sharing dapat diterapkan pada data, termasuk
citra contohnya Visual Cryptography (VC).
Pada penelitian Tugas Akhir ini, ditunjukkan penerapan skema secret sharing
berbasis VC menggunakan citra grayscale bertujuan membuat secret sharing yang
efisien serta merancang skema VC yang dapat mengatasi permasalahan pixel
expansion. Hasil penelitian menunjukkan penerapan skema VC dapat diterapkan
dengan waktu komputasi yang cepat sesuai dengan ukuran pixel dari citra yang
digunakan. Analisis performa dan keamanan terhadap rekonstruksi citra dari skema
VC dilakukan menggunakan metrik, seperti pixel expansion, contrast, kompleksitas
waktu, serta akurasi melalui pengukuran Peak Signal to Noise Ratio (PSNR), Mean
Square Error (MSE), dan Correlation Coefficients (CC), serta melakukan salt and
pepper attack pada hasil skema yang dibuat dan dapat dibuktikan tahan terhadap
salt and pepper attack.
Abstract:
Secret sharing is a scheme that divides a secret value into n shares then each share
is shared with several parties. Each share is unique, requiring at least k shares as
a threshold to reconstruct the original secret. Secret sharing can be applied to data,
including images, for example Visual Cryptography (VC).
In this Final Project research, the application of VC-based secret sharing scheme
using grayscale image is shown to make efficient secret sharing and to design VC
scheme that can overcome pixel expansion problem. The results show that the
application of the VC scheme can be applied with fast computation time according
to the pixel size of the image used. Performance and security analysis of image
reconstruction from the VC scheme is carried out using metrics, such as pixel
expansion, contrast, time complexity, and accuracy through measuring Peak Signal
to Noise Ratio (PSNR), Mean Square Error (MSE), and Correlation Coefficients
(CC), as well as conducting salt and pepper attacks on the results of the scheme
created and can be proven to be resistant to salt and pepper attacks.
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