A data hiding method for JPEG 2000 coded images using modulo arithmetic

Jin, Honglin; Fujiyoshi, Masaaki; Seki, Yusuke; Kiya, Hitoshi

doi:10.1002/ecjc.20286

Cited by 3 publications

References 11 publications

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EMD-based steganography techniques for JPEG2000 encoded images

Kasana

Singh

Bhatia

2017

Int. J. Wavelets Multiresolut Inf. Process.

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In JPEG2000 standard, the number of bit planes of wavelet coefficients to be used in encoding is dependent on the compression ratio as well as subbands. These significant wavelet bit planes can be utilized to embed bits of secret data as they are retained in the final bit stream after Tier-2 encoding. In proposed techniques, the above mentioned concept have been utilized to embed secret data bits in lowest significant bit planes of the quantized wavelet coefficients of a cover image. In first technique, secret data is converted into a series of symbols using multiple bases notational system. These bases are selected by using the degree of local variation of coefficient values of the cover image so that coefficient of a complex region can potentially carry more secret data bits as compared to coefficients of smooth region. Symbols of secret data are embedded into bit planes of significant quantized wavelet coefficients by using EMD approaches. In second technique, the secret data bits are embedded into significant quantized wavelet coefficients by using modified EMD. Experimental results show that these proposed techniques provide large embedding capacity and better visual quality stego images than existing steganography techniques applicable to JPEG2000 compressed images. It has also been shown that modified EMD-based technique is better than EMD with multiple bases notational system (MBNS)-based technique.

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EMD-based steganography techniques for JPEG2000 encoded images

Kasana

Singh

Bhatia

2017

Int. J. Wavelets Multiresolut Inf. Process.

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Secure JPEG2000 Steganography by the Minimization of Code-block Noise Variance Changes

Yoon¹,

Lee²,

Joo³

et al. 2008

The KIPS Transactions:PartC

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JPEG2000 is the upcoming image coding standard that provides better compression rate and image quality compared with JPEG.Lazy-mode steganography guarantees the safe communication under the two information loss stages in JPEG2000. However, it causes the severe changes of the code-block noise variance sequence after embedding and that is detectable under the steganalysis using the Hilbert-Huang transform (HHT) based sequential analysis. In this paper, a JPEG2000 lazy-mode steganography method is presented. The code blocks which produce the sudden variation of the noise variance after embedding are estimated by calculating low precision code-block variance (LPV) and low precision code-block noise variance (LPNV). By avoiding those code-blocks from embedding, our algorithm preserves the sequence and makes stego images secure under the HHT-based steganalytic detection. In addition, it prevents a severe degradation of image quality by using JPEG2000 quality layer information. On various 2048 images, experiments are performed to show the effective reduction of the noise variation after message embedding and the stable performance against HHT-based steganalysis.

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Steganography Encoding as Inverse Data Mining

Ophir

Advances in Systems Analysis, Software Engineering, and High Performance Computing

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Supercomputers and cloud computing seem to be competing paradigms. Supercomputing focuses on increasing CPU speed, thus significantly increasing the speed of its associated memory access and its capacity. Conversely, cloud computing increases the computing throughput by parallel computing, spreading computing tasks over unused nodes and platforms. Steganography, the art of concealing a message within a message, is a type of encoding whose operations are required to remain secret. Steganography encoding requires data manipulation and is linked to data mining methodologies. Data mining reveals concealed data that is embedded in exposed data. Encoding by steganography is reverse data mining, hiding data among visible data. Conventionally, encryption methods are used to successfully hide the data. Cloud computing can take the data and disperse it in a way that even without any encryption, each individual packet of data is meaningless, thus hiding the message as like by steganography. This chapter explores steganography encoding as inverse data mining.

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A data hiding method for JPEG 2000 coded images using modulo arithmetic

Cited by 3 publications

References 11 publications

EMD-based steganography techniques for JPEG2000 encoded images

EMD-based steganography techniques for JPEG2000 encoded images

Secure JPEG2000 Steganography by the Minimization of Code-block Noise Variance Changes

Steganography Encoding as Inverse Data Mining

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