Rights protection for relational data

TLDR

Rights protection for relational data is increasingly important, especially for outsourced sensitive datasets such as those used in data mining, and legal enforcement alone is often ineffective, making digital watermarking a necessary complement. The authors present wmdb, a watermarking‑based solution for protecting relational database content, demonstrated on outsourced Wal‑Mart sales data. wmdb implements a watermarking scheme that embeds protection into relational tables and is applied to real‑world Wal‑Mart sales data. The method preserves higher‑level semantic constraints like classification and withstands attacks including subset selection and random or linear data modifications.

Abstract

we introduce a solution for relational database content rights protection through watermarking. Rights protection for 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 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 counterpart, for example, watermarking. While being able to handle higher level semantic constraints, such as classification preservation, our solution also addresses important attacks, such as subset selection and random and linear data changes. We introduce wmdb., a proof-of-concept implementation and its application to real-life data, namely, in watermarking the outsourced Wal-Mart sales data that we have available at our institute.