On Efficient Constructions and Cheating Prevention of Visual Cryptography
| Autor: | Chih-Ming Hu, 胡智明 |
|---|---|
| Rok vydání: | 2006 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 95 Visual Cryptography (VC) is a method of encrypting a secret image into shares such that stacking a sufficient number of shares reveals the secret image. Shares are usually pesented in transparencies. Each participant holds a transparency. Most of the previous research work on VC focuses on improving two parameters: pixel expansion and contrast. The conventional definition requires that the revealed secret images are always darker than the backgrounds. We observed that this is not necessary, in particular, for the textual images. Therefore, we proposed an improved definition for visual cryptography based on our observation, in which the revealed images may be darker or lighter than the backgrounds. Based on the new definition, we find that many extensions of the original Visual Cryptography Schemes (VCSs) are improvable. According to our study, we improve the results of the original VCSs including the following contributions: 1. We studied properties and obtained bounds for visual cryptography schemes based on the new definition. We proposed methods to construct visual cryptography schemes based on the new definition. 2. We presented three cheating methods and applied them on attacking existent VC or Extended VC (EVC) schemes. We improved one cheat-preventing scheme. We proposed a generic method that converts a VCS to another VCS that has the property of cheating prevention. 3. Based on the new definition, we propose a new ideal VCS with reversing which is compatible and requires fewer stacking and reversing operations, compared to all previous schemes. Each participant is required to store only two transparencies. 4. We propose a (2,$n$)-EVCS scheme based on the new definition. Although the image of this construction is not "smooth", it has better contrast than previous results. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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