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Data Hiding
Data Hiding Algorithm for Images Using Discrete Wavelet Transform and Arnold Transform
Geeta Kasana, Kulbir Singh and Satvinder Singh Bhatia
Page: 1331~1344, Vol. 13, No.5, 2017
10.3745/JIPS.03.0042
Keywords: Arnold Transform, DWT, JPEG, JPEG2000, PSNR, SIM
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Audio Data Hiding Based on Sample Value Modification Using Modulus Function
Mohammed Hatem Ali Al-Hooti, Supeno Djanali and Tohari Ahmad
Page: 525~537, Vol. 12, No.3, 2016
10.3745/JIPS.03.0054
Keywords: Audio, Data Hiding, Modulus Function, Information Security, Network Security
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Hiding Secret Data in an Image Using Codeword Imitation
Zhi-Hui Wang, Chin-Chen Chang and Pei-Yu Tsai
Page: 435~452, Vol. 6, No.4, 2010
10.3745/JIPS.2010.6.4.435
Keywords: Data Hiding, Steganography, Vector Quantization
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Data Hiding Algorithm for Images Using Discrete Wavelet Transform and Arnold Transform
Geeta Kasana, Kulbir Singh and Satvinder Singh Bhatia
Page: 1331~1344, Vol. 13, No.5, 2017

Keywords: Arnold Transform, DWT, JPEG, JPEG2000, PSNR, SIM
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In this paper, data hiding algorithm using Discrete Wavelet Transform (DWT) and Arnold Transform is proposed. The secret data is scrambled using Arnold Transform to make it secure. Wavelet subbands of a cover image are obtained using DWT. The scrambled secret data is embedded into significant wavelet coefficients of subbands of a cover image. The proposed algorithm is robust to a variety of attacks like JPEG and JPEG2000 compression, image cropping and median filtering. Experimental results show that the PSNR of the composite image is 1.05 dB higher than the PSNR of existing algorithms and capacity is 25% higher than the capacity of existing algorithms.
Audio Data Hiding Based on Sample Value Modification Using Modulus Function
Mohammed Hatem Ali Al-Hooti, Supeno Djanali and Tohari Ahmad
Page: 525~537, Vol. 12, No.3, 2016

Keywords: Audio, Data Hiding, Modulus Function, Information Security, Network Security
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Data hiding is a wide field that is helpful to secure network communications. It is common that many data hiding researchers consider improving and increasing many aspects such as capacity, stego file quality, or robustness. In this paper, we use an audio file as a cover and propose a reversible steganographic method that is modifying the sample values using modulus function in order to make the reminder of that particular value to be same as the secret bit that is needed to be embedded. In addition, we use a location map that locates these modified sample values. This is because in reversible data hiding it needs to exactly recover both the secret message and the original audio file from that stego file. The experimental results show that, this method (measured by correlation algorithm) is able to retrieve exactly the same secret message and audio file. Moreover, it has made a significant improvement in terms of the following: the capacity since each sample value is carrying a secret bit. The quality measured by peak signal-to-noise ratio (PSNR), signal-to-noise ratio (SNR), Pearson correlation coefficient (PCC), and Similarity Index Modulation (SIM). All of them have proven that the quality of the stego audio is relatively high.
Hiding Secret Data in an Image Using Codeword Imitation
Zhi-Hui Wang, Chin-Chen Chang and Pei-Yu Tsai
Page: 435~452, Vol. 6, No.4, 2010

Keywords: Data Hiding, Steganography, Vector Quantization
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This paper proposes a novel reversible data hiding scheme based on a Vector Quantization (VQ) codebook. The proposed scheme uses the principle component analysis (PCA) algorithm to sort the codebook and to find two similar codewords of an image block. According to the secret to be embedded and the difference between those two similar codewords, the original image block is transformed into a difference number table. Finally, this table is compressed by entropy coding and sent to the receiver. The experimental results demonstrate that the proposed scheme can achieve greater hiding capacity, about five bits per index, with an acceptable bit rate. At the receiver end, after the compressed code has been decoded, the image can be recovered to a VQ compressed image.