Relational Database Watermarking Clustering Based Data Mining Using K-Means Approach

Database watermark is some kind of information that is embedded into underlying data for tamper detection, maintaining integrity, ownership proof, traitor tracing. It provides copyright protection of relational data and maintaining integrity of the database information. This research we introduced a cluster-based database watermarking technique which first applies cluster theory to the database watermarking technology. The cluster theory is used to cluster the source data and the clustering results determine the quantity of embedded watermark information and embedded position. For embedding watermark odd-even modifying method is apply. This method denoted the watermarking information to decline the modification of original database. This method discards the traditional method to partition subsets. This technique improve the performance on invisibility, gives minimum distortion rate and able to defend all type of subset attacks.