Advancement in information technology is playing an increasing role in the use of information systems comprising relational databases. These databases are used effectively in collaborative environments for information extraction; consequently, they are vulnerable to security threats concerning ownership rights and data tampering. Watermarking is advocated to enforce ownership rights over shared relational data and for providing a means for tackling data tampering. When ownership rights are enforced using watermarking, the underlying data undergoes certain modifications; as a result of which, the data quality gets compromised. Reversible watermarking is employed to ensure data quality along-with data recovery. However, such techniques are usually not robust against malicious attacks and do not provide any mechanism to selectively watermark a particular attribute by taking into account its role in knowledge discovery. Therefore, reversible watermarking is required that ensures; (i) watermark encoding and decoding by accounting for the role of all the features in knowledge discovery; and (ii) original data recovery in the presence of active malicious attacks. In this paper, a robust and semi-blind reversible watermarking (RRW) technique for numerical relational data has been proposed that addresses the above objectives. Experimental studies prove the effectiveness of RRW against malicious attacks and show that the proposed technique outperforms existing ones.
One group of tuples (Nr) is sent for Robust Embedding where a sequence of symbols S1 is embedded into the group for watermarking. The other group (Ng-Nr) is sent for fragile embedding where, the group is embed the model uses a hash function(SHA) to create two groups to be watermarked. Dead with another sequence S2, to allow minimization of data alteration during data reconstruction. During reconstruction, watermarked tuples are identified using primary keys and watermarking key and the original database is retrieved.
EXISTING SYSTEM ARCHITECTURE
DISADVANTAGES OF EXISTING SYSTEM
• Attribute distortion occurs when database size increases
• Carrier groups could be induced with errors such as
The watermark bits are generated from UTC (Coordinated Universal Time). The watermark embedding algorithm takes a secret key (Ks) and the watermark bits (W) as input and converts a data set D into watermarked data set DW. A cryptographic hash function Hmac 256 is applied on the selected data set to select only those tuples which have an even hash value. Image based authentication is used to identify the ownership rights of the user.
ADVANTAGES OF PROPOSED SYSTEM
Distortion of the contents in the database are reduced greatly.
Enhances watermark security by hiding the identity of the watermarked tuples from an intruder.
1. HMAC Sha 256 Algorithm.
System : Pentium IV 2.4 GHz.
Hard Disk : 40 GB.
Floppy Drive : 1.44 Mb.
Monitor : 15 VGA Colour.
Mouse : Logitech.
Ram : 512 Mb.
Operating system : Windows XP.
Coding Language : JAVA
Data Base : MYSQL
R. Agrawal and J. Kiernan, “Watermarking relational databases,” 2. P. E. Gill, W. Murray, and M. A. Saunders, “Snopt: An sqp algorithm for large-scale constrained optimization,” SIAM review, vol. 47, no. 1, pp. 99–131, 2005.