Audio steganography using bit modification

Gopalan, K.

doi:10.1109/icassp.2003.1202390

Cited by 57 publications

(31 citation statements)

References 3 publications

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“…Generally objectives of the LSB-based schemes are to raise payload or the maximum amount of the information to be embedded and to prevent audio quality degradation. This technique is reformed to increase the robustness against additive noise [7].…”

Section: Introductionmentioning

confidence: 99%

Adaptive and efficient audio DataHiding method in temporal domain

Delforouzi

Pooyan

2009

2009 7th International Conference on Information, Communications and Signal Processing (ICICS)

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In this paper a novel Audio steganography method is proposed. In this algorithm, first embedding threshold in the time domain is estimated. Then this threshold is used for data concealment in the time domain. The performance of the proposed scheme in terms of SNR (signal to noise ratio) and BER (bit error rate) is analyzed. An estimation formula that connects SNR with embedding threshold has been provided to ensure the transparency of embedded data. The security of this method is enhanced by using of an encryption method prior to the data embedding step. Proposed scheme is a high velocity method because of its implementation in the temporal domain. Experimental results demonstrate that the proposed method has high payload, full and blind recovery and high audio quality.

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Section: Introductionmentioning

confidence: 99%

Adaptive and efficient audio DataHiding method in temporal domain

Delforouzi

Pooyan

2009

2009 7th International Conference on Information, Communications and Signal Processing (ICICS)

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“…In recent years various techniques for steganography in digital audio with varying purposes have been developed [1][2][3][4][5][6][7][8][9]. These methods use characteristics (weakness) of the human auditory system (HAS).…”

Section: Introductionmentioning

confidence: 99%

“…Generally objectives of the LSB-based schemes are to raise the payload or the maximum amount of information to be embedded and to prevent audio quality degradation. This technique has also been reformed to increase the robustness against additive noise [6].…”

Section: Introductionmentioning

confidence: 99%

Adaptive Digital Audio Steganography Based on Integer Wavelet Transform

Delforouzi

Pooyan

2008

Circuits Syst Signal Process

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In this paper a novel method for digital audio steganography is presented where encrypted covert data is embedded into the coefficients of the host audio (cover signal) in the integer wavelet domain. The hearing threshold is calculated in the integer domain and this threshold is employed as the embedding threshold. The inverse integer wavelet transform is applied to the modified coefficients to form a new audio sequence (stego signal). The characteristics of this method are large payload, high audio quality and full recovery.

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“…Instead of protecting data the way encryption does, steganography hides the existence of the data (Provos and Honeyman, 2003). Most of the steganography study has been carried out on pictures (Chandramouli and Memon, 2001;Shirali, 2005) video clips (Doërr and Dugelay, 2003;Doërr and Dugelay, 2004), music and sounds (Gopalan, 2003). Text steganography is the most difficult kind of steganography this is due largely to the relative lack of redundant information in a text file as compared with a picture or a sound file (Bender et al, 1996).…”

Section: Introductionmentioning

confidence: 99%

Text Hiding in Mobile Phone Simple Message Service Using Fonts

Bhaya¹

2011

Journal of Computer Science

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Problem statement: Hiding secret information in an ordinary mobile phone Simple Message Service (SMS). Approach: In mobile phones, there are two default types of fonts, System and Proportional fonts, which have similar figures to human vision and cannot recognized by human eye. The suggested method hides the information (0,1) in cover SMS message by changing the fonts of each character by one of those two fonts (0 represented by System font and 1 represented by Proportional fonts). After embedding secret information in cover message, the Stego message will look like an ordinary message but each character draw in one of these similarity fonts. Finally, at extract site, it must analyze each character font to retrieve secret information. This study has been implemented by J2ME (Java 2 Micro Edition) programming language to works in mobile (cellular) phones. Results: By using two similarity fonts, we can hide one bit in one character of mobile phone message. Conclusion: Good steganography depends on the human behavior and way of thinking. The most successful hiding method is the uncommon one. Although the proposed method is simple but it is unthinkable one and needs knowledge and experience to be discovered.

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Audio steganography using bit modification

Cited by 57 publications

References 3 publications

Adaptive and efficient audio DataHiding method in temporal domain

Adaptive and efficient audio DataHiding method in temporal domain

Adaptive Digital Audio Steganography Based on Integer Wavelet Transform

Text Hiding in Mobile Phone Simple Message Service Using Fonts

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