Watermarking Audio Signals for Copyright Protection Using ICA

Watermarking Audio Signals for Copyright Protection Using ICA

B. R. Matam, David Lowe
Copyright: © 2010 |Pages: 14
DOI: 10.4018/978-1-61520-903-3.ch007
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Abstract

The protection or tracking of content transmitted via digital time series data is an important and under-researched area of watermarking. In this chapter a discussion of information hiding in the context of copyright protection of audio signals, an example of time series data is presented. Independent component analysis (ICA) based watermarking methods are used to embed copyright information. The integrity of a hidden message when the cover text in which it is hidden, is attacked by applying signal processing techniques such as filtering and addition of noise to the signal will be investigated. The results of the application of the ICA based method are compared with the results of the application of the discrete wavelet transform (DWT) based approach. This chapter reveals the advantages of using a data dependent transform (for example ICA) based watermarking method for copyright applications when compared with static transform domain (having fixed coefficients, for example DWT) based methods.
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Background

Examples of cryptography (data encryption) and steganography (data hiding) can be traced back to a period between 600BC and 400BC (see references within (Petitcolas, 2000)). The difference between the two methods being cryptography (Stallings, 2003) renders messages unintelligible to unauthorized persons who intercept them while steganography conceals the message itself from unauthorized persons (Petitcolas et. al. 1998). In cryptography the attacker knows that information is being transmitted and the security of the encryption method relies on the complexity (time and resources required) of the method used to estimate the key that is required to decipher the message. In steganography, the information is hidden in the sense that it is perceptually and statistically undetectable. The attacker's challenge is to not only identify the transmission of the hidden message but also to detect the location and if possible retrieve the hidden information.

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