Dataset Watermarking Using the Discrete Wavelet Transform

Conference Paper (2025)
Author(s)

Mike P. Raave (Student TU Delft)

Devri İş Ler (IMDEA Networks Institute, Carlos III University of Madrid)

Zekeriya Erkin (TU Delft - Cyber Security)

Faculty
Electrical Engineering, Mathematics and Computer Science
DOI related publication
https://doi.org/10.5220/0013556300003979
More Info
expand_more
Publication Year
2025
Language
English
Faculty
Electrical Engineering, Mathematics and Computer Science
Pages (from-to)
676-681
ISBN (print)
9789897587603

Abstract

In this work, we focus on watermarking time series datasets and explore one of the techniques known from audio-watermarking, namely Discrete Wavelet Transform (DWT) based watermarking, to investigate its effectiveness. We adapt (Attari and A. Shirazi, 2018) and embed a bit stream into a time series dataset by calculating the DWT coefficients and modifying their magnitudes for embedding. Our experimental results on two real-world datasets show good robustness against a small range of data modification attacks but lack capability in larger-scale attacks. We believe that our work could initiate a new research direction on dataset watermarking using well-known techniques from signal processing.

No files available

Metadata only record. There are no files for this record.