Watermarking Scheme with CS Encryption for Security and Piracy of Digital Audio Signals

Watermarking Scheme with CS Encryption for Security and Piracy of Digital Audio Signals

Rohit Thanki (C. U. Shah University, Wadhwan City, India) and Komal Borisagar (Atmiya Institute of Technology and Science, Rajkot, India)
Copyright: © 2017 |Pages: 23
DOI: 10.4018/IJISMD.2017100103

Abstract

In this article, a watermarking scheme using Curvelet Transform with a combination of compressive sensing (CS) theory is proposed for the protection of a digital audio signal. The curvelet coefficients of the host audio signal are modified according to compressive sensing (CS) measurements of the watermarked data. The CS measurements of watermark data is generated using CS theory processes and sparse coefficients (wavelet coefficients of DCT coefficients). The proposed scheme can be employed for both audio and speech watermarking. The gray scale watermark image is inserted into the host digital audio signal when the proposed scheme is used for audio watermarking. The speech signal is inserted into the host digital audio signal when the proposed scheme is employed for speech watermarking. The experimental results show that proposed scheme performs better than the existing watermarking schemes in terms of perceptual transparency.
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1. Introduction

The multimedia data such as images, videos, and audios are easily downloadable when transmitted over the internet. The duplication of this data is often possible without giving credits to the original creators. This situation creates the problem of owner authentication and protection. The watermarking technique provides one of the solutions for these issues. Many researchers have proposed various watermarking schemes for owner protection of data which is transferred over the non-secure communication channel.

The watermarking technique can be divided into various types such as image watermarking, video watermarking, audio watermarking, biometric watermarking, and medical watermarking (Langelaar et al., 2000; Jain and Uludag, 2003; Thanki and Kothari, 2016; Ashour and Dey, 2017; Borra et al., 2017; Borra and Swamy, 2013, 2012, 2011; Dey et al., 2017; Parah et al., 2017; Rajeswari et al., 2017). Most watermarking techniques are designed and analyzed for digital images and video protection. There are various types of watermarking techniques such spatial domain watermarking, transform domain watermarking and sparse domain watermarking (Langelaar et al., 2000; Sheikh and Baraniuk, 2007). The spatial domain watermarking has less secured against watermarking attack. While transform watermarking has more secured against watermarking attack but have less payload capacity. The sparse domain watermarking techniques are new watermarking techniques which were utilized Compressive Sensing (CS) theory (Donoho, 2006; Candes, 2006) with watermarking. This technique is mainly used data authentication and provided more payload capacity compared to other watermarking techniques.

There are various watermarking techniques are proposed by researchers for the security of audio data, image data, and speech data in last ten years. Here watermarking techniques which are related to proposed scheme are reviewed in two categories. In the first category, give information about watermarking techniques, where the audio signal was used as host medium and watermark data, can be an image. These are known as audio watermarking techniques. In the second category, give information about watermarking techniques where the speech signal was used as watermark data and host medium can be a digital image or audio signal. These are known as speech watermarking techniques.

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