Watermarking Relational Databases Using Optimization-Based Techniques(2008)

Abstract:

Proof of ownership based on the secure embedding of a robust imperceptible watermark in relational data. We formulate the watermarking of relational databases as a constrained optimization problem and discuss efficient techniques to solve the optimization problem and to handle the constraints. Watermark decoding is based on a threshold-based technique characterized by an optimal threshold that minimizes the probability of decoding errors. We implemented a proof of concept implementation of our watermarking technique and showed by experimental results that our technique is resilient to tuple deletion, alteration, and insertion attacks. A watermark describes information that can be used to prove the ownership of data such as the owner, origin, or recipient of the content. We develop an efficient technique for watermark detection that is based on an optimal threshold. The optimal threshold is selected by minimizing the probability of decoding error.

Existing System:           

            Watermarking techniques have emerged as an important building block that plays a crucial role in addressing the ownership problem. Such techniques allow the owner of the data to embed an imperceptible watermark into the data. A watermark describes information that can be used to prove the ownership of data such as the owner, origin, or recipient of the content. Secure embedding requires that the embedded watermark must not be easily tampered with, forged, or removed from the watermarked data.

Proposed System:

We present a watermarking technique for relational data that is highly resilient compared to these techniques. In particular, our proposed technique is resilient to tuple deletion, alteration, and insertion attacks. Formulate the watermarking of relational databases as a constrained optimization problem and discuss efficient techniques to handle the constraints. There are two techniques to solve the formulated optimization problem based on genetic algorithms and pattern search techniques. Proposed system present a data partitioning technique that does not depend on marker tuples to locate the partitions and, thus, it is resilient to watermark synchronization errors. We develop an efficient technique for watermark detection that is based on an optimal threshold. The optimal threshold is selected by minimizing the probability of decoding error.

Modules:

Module Description

1. Data Insertion

Data insertion module contains three applications for collecting data from admin side. First one is “stock information” second one is “weather report” and third one is “medical research”. In stock information module admin will insert details about the company and final stock range of these companies. Each and every changes of the stock details should updated by admin. Like these weather report and medical research details should contain the institute name and updated details. This module fully handled by the admin side. After this process it will goes to watermark embedded process.

2. Watermark Embedded

This port is main role of this project. Here we are going to apply watermark technique to our given input. After apply the watermark technique the data will hided. The hided data we will send through network with watermark key. So, we should generate one watermark key for every data. Finally the watermarked data and the key will send to destination through network.

3. Watermark Detection

Detecting or retrieving the embedded data is the main role of this module. At the time of retrieval process it should want watermark key for receive the original data. Here first we will check access permission of the end users, based on their username and password. If the users has admin role [receiver side] they will access the data and then save it with the help of watermark key. If the users has end user role [visitors] they can only view the data from receiver side admin. If hackers want to access our data in-between the network, our application will check the access permission and the key. Hackers come under the end user mode so they can’t access the data without help of administrator.

HARDWARE AND SOFTWARE REQUIREMENTS

Software Requirements:

Language                       :   C#.NET

Technologies                 :  Microsoft.NET Framework,ASP.NET,ADO.NET

IDE                                   :  Visual Studio 2008

Backend                         :  SQL Server 2005

Operating System        :  Microsoft Windows XP SP2 or Later Version

Hardware Requirements:

Processor                        : Intel Pentium or more

RAM                                   : 512 MB (Minimum)

Hard Disk                         : 40 GB