Novel Method for Watermarking Outsources Dataset by Using Usability Constraint

The large datasets are being mined to extract hidden knowledge and patterns that assist decision makers in making effective, efficient, and timely decisions in an ever increasing competitive world. This type of “knowledge discovery driven� data mining activity is not possible without sharing the “datasets� between their owners and data mining experts as a consequence, protecting. Usually, an owner needs to manually define “Usability limitations� for each type of dataset to preserve the contained knowledge. The major contribution of this paper is a novel formal model that facilitates a data owner to define usability limitations to preserve the knowledge contained in the dataset in an automated fashion. The model aims at preserving “classification potential� of each feature and other major characteristics of datasets that play an important role during the mining process of data; as a result, learning statistics and decision-making rules also remain intact. We have implemented our model and integrated it with a new watermark embedding algorithm to prove that the inserted watermark not only preserves the knowledge contained in a dataset but also significantly enhances watermark security compared with existing techniques. We have tested our model on more than twenty five different data mining datasets to show its efficacy, effectiveness, and the ability to adapt and simplify.