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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 beproven to be resistant to salt and pepper attacks.
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