Watermarking time-series data using DWT

Abstract

Data security has become more important over the last few years as data sharing over the world has become trivial. Data ownership therefore becomes critical as data can be very valuable and vulnerable to theft. Watermarking is a technique that can help data owners prove ownership over their data. In this paper, an approach is presented to watermark data that is gathered over time, such as weather data. With this research, we propose an adaptation of an existing audio watermarking technique developed in [1]. The adapted algorithm embeds a bit stream into a non-medical time series dataset by calculating the Discrete Wavelet Transform coefficients and modifying their magnitudes. The algorithm shows good robustness against a small range of data modification attacks but lacks capability in larger
scaled attacks. In addition, the proposed algorithm does require additional research to use it in a professional setting.