Abstract
Protecting rights over relational data is of ever increasing interest, especially considering areas where sensitive, valuable content is to be outsourced. A good example is a data mining application, where data is sold in pieces to parties specialized in mining it.
Different avenues for rights protection are available, each with its own advantages and drawbacks. Enforcement by legal means is usually ineffective in preventing theft of copyrighted works, unless augmented by a digital counter-part, for example watermarking.
Recent research of the authors introduces the issue of digital watermarking for generic number sets. In the present paper we expand on this foundation and introduce a solution for relational database content rights protection through watermarking.
Our solution adresses important attacks, such as data re-sorting, subset selection, linear data changes (applying a linear transformation on arbitrary subsets of the data). Our watermark also survives up to 50% and above data losses.
Finally we present wmbd.*, a proof-of-concept implementation of out algorithm and its application to real life data, namely in watermarking the outsourced Wal-Mart sales data that we have available at our institute.
