Shamir Secret Sharing Based Authentication Method with Data Repair Capability for Gray Scale Document Images via the Use of PNG Image
| ||International Journal of Computer Trends and Technology (IJCTT)|| |
|© - November Issue 2013 by IJCTT Journal|
|Volume-5 Issue-1 |
|Year of Publication : 2013|
|Authors :Nagababu Manne , K.J.Silva Lorraine.|
Nagababu Manne , K.J.Silva Lorraine."Shamir Secret Sharing Based Authentication Method with Data Repair Capability for Gray Scale Document Images via the Use of PNG Image"International Journal of Computer Trends and Technology (IJCTT),V5(1):37-43 November Issue 2013 .ISSN 2231-2803.www.ijcttjournal.org. Published by Seventh Sense Research Group.
Abstract:- Generally digital images are mostly used to preserve confidential & important information. But the problem is providing authentication and integrity to these digital images is a very challenging task. Therefore using this paper a new efficient authentication method is proposed to provide for grayscale document images using the Portable Network Graphics (PNG) image with data repair capability. In this concept an authentication signal generated by each block of a grayscale document image and then using Shamir secret sharing scheme grayscale document image authentication signal and binarized block content is combined and transformed into several shares. These several binarized block content shares are then combined into an alpha channel plane then the PNG image is built from combining the grayscale image with alpha channel plan. In this process the authentication for image is achieved as follows; if the authentication signal measured from the current block content does not match that extracted from the shares embedded in the alpha channel plane then that image block is tampered. Then using reverse Shamir scheme, two shares from unmarked blocks are collected and then data repairing is applied. Finally simulation results are provided to prove the concept of proposed method.
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Keywords :— Evolving fuzzy systems, fuzzy-rule-based (FRB) classifiers, user modeling.