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https://elibrary.tucl.edu.np/handle/123456789/10704
Title: | Comparative Analysis of Visual Secret Sharing Cryptography Scheme: Shamir's Secret Sharing and Proactive Secret Sharing |
Authors: | Regmi, Bikash |
Keywords: | Share generation;Share reconstruction;Shamir's secret share;Proactive secret share scheme |
Issue Date: | 2019 |
Publisher: | Department of Computer Science & Information Technology |
Institute Name: | Central Department of Computer Science and Information Technology |
Level: | Masters |
Abstract: | Visual secret share scheme plays an important role in area of information security. Different from conventional cryptography, visual cryptography is an image cryptographic technique proposed by Naor and Shamir which encodes a secret image into multiple shares. When defined minimum threshold number of shares are gathered from shared participant's share can reveal the secret image. This phenomenon is also known as (k, n) threshold secret share scheme. Visual cryptography schemes allow the encoding of a secret image into shares, which are distributed to the participants. The requirement for minimum threshold share ultimately leads to the confidentiality of secret. (k, n) visual secret sharing uses threshold scheme by using the concept of Lagrange's polynomial interpolation. Applying XOR operation with cover image leads to authentication of secret. The reconstruction of the original image without loss of information can be generated from shared shares using the concept of Lagrange's polynomial interpolation. In this study visual secret share scheme by using Shamir's Secret Share Scheme and Proactive Secret Share Scheme are implemented and analyzed with different parameter like NPCR, UACI, correlation-coefficient, performance speed measures. Based on UACI and correlation-coefficient results Proactive Secret Share scheme has better performance whereas based on the NPCR and Computational time results Shamir's Secret Share scheme showed better performance. |
URI: | https://elibrary.tucl.edu.np/handle/123456789/10704 |
Appears in Collections: | Computer Science & Information Technology |
Files in This Item:
File | Description | Size | Format | |
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Full Thesis.pdf | 3.43 MB | Adobe PDF | View/Open |
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