University of Twente Student Theses


A comparative analysis of audio steganography methods and tools

Reyers, P.M. (2023) A comparative analysis of audio steganography methods and tools.

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Abstract:Steganography is the process of hiding data within other data. Unlike cryptography which aims to secure data through obscuring its meaning, steganography aims to secure data by obscuring its existence altogether. Although many different types of cover data, such as text or images, can be used to embed secret data in, this paper focuses on audio steganography because it is uniquely positioned to enabled real time secure communication. A problem within currently available audio steganography research is that there are no thorough comparative analyses available of modern audio steganography methods, such as machine learning based methods. While such comparative analyses are available for many other types of steganography, such as image steganography. The origin of this problem can be partially attributed to the fact that there is a wide variety of evaluation features and audio datasets in use among audio steganography researchers. This makes it difficult to directly compare the results of two different papers. To address this problem, this paper provides a comparative analysis of two methods proposed in the last 5 years (An Audio Steganography Method Based on generative adversarial networks (GAN), and Logistic Tan Map Based Audio Steganography) and two popular steganography tools (Hide4PGP, Steghide) that have existed for over a decade. This analysis was performed using three evaluation features (Bit Error Rate (BER), Signal to Noise Ratio (SNR), Embedding Percentage (EP)) and three datasets (TIMIT, GZTAN, ESC50). These were selected to be most suitable for the evaluation of steganography research based on criteria formed after thorough review of the ones most commonly found in audio steganography research. This comparative analysis and the datasets/evaluation features recommendation is important because it will help future searchers in more consistently evaluating their audio steganography methods and understand those evaluation results in the context of the performance of other methods. It also helps shed light on the performance of new methods in comparison to the old existing tools.
Item Type:Essay (Bachelor)
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:54 computer science
Programme:Computer Science BSc (56964)
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