A novel quantum steganography-Steganalysis system for audio signals

Chaharlang, Javad; Mosleh, Mohammad; Heikalabad, Saeed Rasouli

doi:10.1007/s11042-020-08694-z

Cited by 21 publications

(8 citation statements)

References 52 publications

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“…BER is a metric used to calculate the correctness of embedding; it shows the percentage of the message bits that was retrieved incorrectly, as expressed by equation 7 [57][58]:…”

Section: ) Bit Error Rate (Ber)mentioning

confidence: 99%

Enhancing LSB Using Binary Message Size Encoding for High Capacity, Transparent and Secure Audio Steganography–An Innovative Approach

Mahmoud

Elshoush

2022

IEEE Access

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We propose a novel LSB-BMSE method that enhances LSB audio steganography. It uses an innovative mechanism, Binaries of Message Size Encoding (BMSE), to embed a secret message after hiding its size in random samples. First, the secret message is compressed using Huffman coding, then encrypted by AES-128. The audio cover is split into number of blocks depending on secret message size. A secure key BMSE , output from the BMSE mechanism, is used to embed the secret message in random blocks and bytes adaptively according to its size. It is implemented using MATLAB and standard parameters: Perceptual Evaluation of Speech Quality and NIST Statistical Test Suite were used to measure imperceptibility between cover & stego audios and randomness of BMSE mechanism respectively. The fidelity was tested using Mean Square Error, Peak Signal to Noise Ratio and Signal-to-Noise Ratio. Comprehensive experiments on widely used metrics demonstrate that LSB-BMSE significantly surpasses existing methods in terms of hiding capacity and imperceptibility. Moreover, LSB-BMSE shows resistance to brute force attacks and statistical analysis. Although it was robust towards re-sampling attacks, nevertheless was not vigorous towards noise nor LSB attacks. The key BMSE complies with Kerckhoff's principle and exhibits avalanche criteria. The tested proposed LSB-BMSE proclaimed its effectiveness.

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“…BER is a metric used to calculate the correctness of embedding; it shows the percentage of the message bits that was retrieved incorrectly, as expressed by equation 7 [57][58]:…”

Section: ) Bit Error Rate (Ber)mentioning

confidence: 99%

Enhancing LSB Using Binary Message Size Encoding for High Capacity, Transparent and Secure Audio Steganography–An Innovative Approach

Mahmoud

Elshoush

2022

IEEE Access

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“…The DWT and singular value decomposition (SVD) techniques have been utilized in the proposed watermarking scheme; this proposed decentralized watermarking works based on distributing the audio signal watermark into the corners of the host signals for enhancing the robustness of this decentralized watermarking technique [26]. Furthermore, based on the LSB algorithm in [27], the steganography technique is proposed for image embedding into audio files. This approach contains two processes, the compression and encryption process of the image by the GMPR technique.…”

Section: Related Workmentioning

confidence: 99%

“…This approach contains two processes, the compression and encryption process of the image by the GMPR technique. Examples of data hiding techniques utilized as a tool for image and audio security have been presented in several research papers [26][27][28].…”

Section: Related Workmentioning

confidence: 99%

Secure Audio Transmission Over Wireless Uncorrelated Rayleigh Fading Channel

Faragallah¹,

Farouk²,

El‐Sayed³

et al. 2022

Computers, Materials &Amp; Continua

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Audio communications and computer networking play essential roles in our daily lives, including many domains with different scopes. Developments in these technologies are quick. In consequence, there is a dire need to secure these technologies up to date. This paper presents an efficient model for secure audio signal transmission over the wireless noisy uncorrelated Rayleigh fading channel. Also, the performance of the utilized multiple secret keys-based audio cryptosystem is analyzed in different transformation domains. The discrete cosine transform (DCT), the discrete sine transform (DST), and the discrete wavelet transform (DWT) are investigated in the utilized multiple secret key-based audio cryptosystem. Simulation results show consistent results with the wireless noisy channel. The performance of the proposed multiple secret keys-based audio cryptosystem can be ranked concerning the employed domain as DWT, DCT, and DST transform techniques. The simulation experiments proved that the presented multiple secret keysbased audio cryptosystem for audio signals transmitted over the wireless noisy uncorrelated Rayleigh fading channel achieves reliable and secure wireless link utilizing combined multi security layers.

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“…The audio cryptosystem used in recent research [7] can be represented as shown in Fig. 2, and it discussed the results based on time-domain (TD), discrete cosine transform (DCT) [22][23][24][25] and discrete sine transform (DST). As depicted in Fig.…”

Section: Baker Mapmentioning

confidence: 99%

Secret Key Optimization for Secure Speech Communications

Faragallah¹,

Farouk²,

El‐Sayed³

2022

Computers, Materials &Amp; Continua

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This paper answers three essential questions for audio speech cryptosystems in time and discrete transform domains. The first question is, what are the best values of sub-keys that must be used to get the best quality and security for the audio cryptosystem in time and discrete transform domains. The second question is the relation between the number of sub-keys, the number of secret keys used, and the audio speech signal block's size. Finally, how many possible secret keys can be used to get the best quality and security results for the audio speech cryptosystem in time and discrete transform domains. An audio cryptosystem discussed before in recent research is applied to answer the three previous inquiries. Accurate simulation results and analysis answer all three questions; first, there is no specific, well-defined format or rule for sub-key values that must be used to get a better cryptosystem. For the second question, yes, there is a direct relationship between the number of applicable keys, number of available sub-keys, and block size of speech audio signal and formulated into a first-order equation. For the third question, each discrete transform domain has a specific acceptable range of sub-keys that imply a particular number of keys that can be used to get a better cryptosystem.

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A novel quantum steganography-Steganalysis system for audio signals

Cited by 21 publications

References 52 publications

Enhancing LSB Using Binary Message Size Encoding for High Capacity, Transparent and Secure Audio Steganography–An Innovative Approach

Enhancing LSB Using Binary Message Size Encoding for High Capacity, Transparent and Secure Audio Steganography–An Innovative Approach

Secure Audio Transmission Over Wireless Uncorrelated Rayleigh Fading Channel

Secret Key Optimization for Secure Speech Communications

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