EMD-based steganography techniques for JPEG2000 encoded images

Steganography is the process of embedding data into a media form such as image, voice, and video. The major methods used for data hiding are the frequency domain and the spatial domain. In the frequency domain, the secret data bits are inserted into the coefficients of the image pixel's frequency representation such as Discrete Cosine Transform (DCT) , Discrete Fourier Transform (DFT) and Discrete Wavelet Transform (DWT) . On the other hand, in the spatial domain method, the secret data bits are inserted directly into the images' pixels value decomposition. The Lest Significant Bit (LSB) is consider as the most widely spatial domain method used for data hiding. LSB embeds the secret message's bits into the least significant bit plane( Binary decomposition) of the image in a sequentially manner . The LSB is simple, but it poses some critical issues. The secret message is easily detected and attacked duo to the sequential embedding process. Moreover, embedding using a higher bit plane would degrade the image quality. In this paper, we are proposing a novel data hiding method based on Lucas number system. We use Lucas number system to decompose the images' pixels values to allow using higher bit plane for embedding without degrading the image's quality. The experimental results show that the proposed method achieves better Peak Signal to Noise Ratio ( PSNR) than the LSB method for both gray scale and color images. Moreover, the security of the hidden data is enhanced by using Pseudo Random Number Generators(PRNG) for selecting the secret data bits to be embedded and the image's pixels used for embedding.

Steganography algorithms used to secure sensitive data on the Internet. It hides the secret data in the cover image and provides imperceptibility to the attacker. The least significant bit (LSB) is the most preferred data hiding technique in the steganography. In this technique, the least significant bit of the cover image pixel replaced with data bits. In the literature, the data hiding achieved without considering the human visual system (HVS) characteristics that degrade the visual quality of the image. In this paper, the optimized data hiding has done while considering the HVS characteristics. The colour image contains three planes known as the red–green–blue plane. The green plane is the most sensitive, and blue is less sensitive to the human eyes. Thus, in the proposed technique, the green plane used as a reference plane for data hiding in the red and blue planes. In the optimized data hiding technique, the secret data bits match with the cover pixel bits. If the bits match, then the corresponding optimal index determines, else data hiding done in the LSB bits of the cover pixel. After that, the optimal indexes hide in the cover image using a 2-bit LSB technique. In the proposed technique, image smooth and edge region characteristics explored before data hiding. There is a high correlation between the consecutive pixels in the smooth region and the minimum correlation on the edges. Thus, we have matched the secret data bits with the cover pixel bits in the smooth region and hide the optimal indexes on the edges. The experimental results performed on the standard dataset images downloaded from the USC-SIPI image database. The experimental results show that the proposed technique provides better visual quality as compared to the existing techniques.

The secure communication of information is a major concern over the internet. The information must be protected before transmitting over a communication channel to avoid security violations. In this paper, a new hybrid method called compressed encrypted data embedding (CEDE) is proposed. In CEDE, the secret information is first compressed with Lempel Ziv Welch (LZW) compression algorithm. Then, the compressed secret information is encrypted using the Advanced Encryption Standard (AES) symmetric block cipher. In the last step, the encrypted information is embedded into an image of size 512 × 512 pixels by using image steganography. In the steganographic technique, the compressed and encrypted secret data bits are divided into pairs of two bits and pixels of the cover image are also arranged in four pairs. The four pairs of secret data are compared with the respective four pairs of each cover pixel which leads to sixteen possibilities of matching in between secret data pairs and pairs of cover pixels. The least significant bits (LSBs) of current and imminent pixels are modified according to the matching case number. The proposed technique provides double-folded security and the results show that stego image carries a high capacity of secret data with adequate peak signal to noise ratio (PSNR) and lower mean square error (MSE) when compared with existing methods in the literature.

An adaptive steganographic method based on the measurement of just noticeable distortion profile

Reversible Data Hiding (RDH) should be secured as per requirements to protect content in open environments such as the cloud and internet. Integrity and undetectability of steganographic images are amongst the main concerns in any RDH scheme. As steganographic encryption using linear prediction over bit-planes is challenging, so the security and embedding capacity of the existing RDH techniques could not be adequate. Therefore, a new steganographic technique is proposed which provides better security, higher embedding capacity and visual quality to the RDH scheme. In this technique, the cover image is divided into n-bit planes (nBPs) and linear prediction is applied to it. Next, the histogram of the residual nBPs image is taken, and secret data bits are encrypted using the RC4 cryptographic algorithm. To embed the encrypted secret data bits, the histogram shifting process is applied. This is achieved by using peak and zero pairs of residual nBPs images. This scheme provides security to the cover image and hidden data. The proposed RDH scheme is capable of extracting the embedded secret data accurately and recovering the original cover or residual nBPs image.

Being lossless, Reversible Image Watermarking (RIW) with Difference Expansion (DE) algorithm is crucial for content authentication, especially for high security medical and military images. In DE-RIW, the secret data bit can be embedded into the Least Significant Bit (LSB) of the difference between two neighboring pixels. Very few researchers have worked on High Level Synthesis (HLS) based implementation of its modified algorithm on Field Programmable Gate Array (FPGA) and Programmable System-On-Chip (P-SoC). Here, to get accelerated performance a modified DE-RIW algorithm is proposed along with its VLSI based hardware implementation both on Xilinx FPGA and P-SoC. In the proposed approach, scheduling is done considering resource constraint criteria. Implementation results through simulation up to burning the design on board needs fewer resources (adder, subtractor, multiplier, divider, register, multiplexer, and comparator) as compared with the similar existing architectures in the literature based on RIW.

A secure image steganography based on LSB technique and 2D chaotic maps

Digital Image Steganography Using Variable Length Group Of Bits Substitution

Nowadays since the Internet is ubiquitous, the frequency of data transfer through the public network is increasing. Hiding secure data in these transmitted data has emerged broad security issue, such as authentication and copyright protection. On the other hand, considering the transmission efficiency issue, image transmission usually involves image compression in Internet-based applications. To address both issues, this paper presents a data hiding scheme for the image compression method called absolute moment block truncation coding (AMBTC). First, an image is divided into non-overlapping blocks through AMBTC compression, the blocks are classified four types, namely smooth, semi-smooth, semi-complex, and complex. The secret data are embedded into the smooth blocks by using a simple replacement strategy. The proposed method respectively embeds nine bits (and five bits) of secret data into the bitmap of the semi-smooth blocks (and semi-complex blocks) through the exclusive-or (XOR) operation. The secret data are embedded into the complex blocks by using a hidden function. After the embedding phase, the direct binary search (DBS) method is performed to improve the image quality without damaging the secret data. The experimental results demonstrate that the proposed method yields higher quality and hiding capacity than other reference methods.

Pixel Value Ordering (PVO) is a data hiding technique through which pixels within an image block are ranked and modify minimum or maximum pixel value for data embedding. In this paper, we proposed an Extended Directional Improved PVO (EDIPVO) for Reversible Data Hiding (RDH) scheme. The original image pixel blocks are interpolated by inserting extra pixels between each row and each column. During data embedding, we consider a parameter \((\alpha )\), perform addition with maximum pixel value, and subtract \(\alpha \) from minimum pixel value to maintain the order within the pixel block. The parameter \(\alpha \) is dependent on the size of the original image block. To increase data hiding capacity, we have considered pixel ranking in three different directions: (1) horizontal, (2) vertical, and (3) diagonal within each block. The secret data bits are embedded starting from the largest, second largest, and so on for maximum value modification and smallest, second smallest, and so on for minimum value modification. The data embedding capacity has been improved than previous data hiding schemes while keeping visual quality unaltered. Experimental results are compared with existing state-of-the-art methods and achieve good results.

This paper deals with hash based secure chaotic steganography technique for hiding secret information, into the cover image. Hash function has been used in the proposed work for computing the Non LSB positions for hiding the secret data bits. Secret is encoded with chaotic sequences and randomness of the sequences has been validated with NIST test suite. Shared memory implementation for faster execution of the proposed security technique has been done in OpenMP platform. Sequential and the parallel versions of the techniques have been implemented in C++, OpenMP and simulated in the Intel Haswell processor based multi-core environment. With the advantages offered by multicore processors the proposed technique ensures low time complexity. Significant speedup and linear scalability have been reported with increase in the number of threads. Standard statistical validation test results viz. PSNR, Euclidean distance, histogram analysis, SSIM index applied to validate the quality of stego image show satisfactory results.

Medical records are extremely sensitive information and may cause a violation of patients' rights if the data is captured or altered. Such data requires uncompromising security during transmission or when the data is stored in medical datacenters. The most commonly used procedure is to hide sensitive information inside a cover medium without incurring any increase in data size or computational overhead. Even though many steganography techniques have been proposed in recent years, only a few have addressed issues related to protecting medical data. In this paper, we proposed a data hiding method based on magic cube generated using magic matrix. In the proposed method, 9 bits of secret data were embedded in each group of 4 pixels using secret keys that scattered values in the square template to make it more unpredictable. Experimental results showed that the proposed method achieved an embedding capacity of 2.25 bpp and an average PSNR of 44 dB outperforming previous methods.

With the rapid advance in digital network, information technology, digital libraries, and particularly World Wide Web services, many kinds of information could be retrieved any time. So in this digital scenario invisible communication between two parties is the prime concern. Steganography is the technique of hidden communication. It not only hides the message contents, instead it hides the existence of the message. In this paper, a new image steganography method based on spatial domain is proposed secret data hided in image segments using least significant bit (LSB) steganography is proposed. The color image is divided into four equal parts and the secret data is also divided into four equal parts and those divided data is hided in the image segments using least significant bit steganography. In this paper we have critically analyzed various steganographic techniques and also have covered steganography overview its major types, classification, applications.

Performing secure and robust embedding and extracting in real time voice streams without deteriorating the voice quality is a great challenge. This paper aims on hiding the secret data bits in the voice packets without modifying any data in the cover thereby improving the embedding transparency and becomes robust against the steganalysis attacks using coverless approach. Initially a hash array is built with the frame size. The cover bit position is identified from the hashing function. The hash array is marked with a flag value to indicate that the particular sample consist of the secret message bit. The hash array is attached with the VoIP samples, at the receiver side the hash table is separated, and the secret bits are extracted based on the hash array. The experimental results conducted on a VoIP prototype proved to be simpler and effective in terms of the computational complexity, undetectability and voice quality at both sender and receiver end.

Transmission of information through the internet can involve sensitive personal data that can be tapped, there are many applications and websites that require good security to avoid the safety of theft of documents and confidential information. Stegnography is the art and science of writing stored secret messages that are not separate from the sending and the recipient is asked related to hidden messages, images as one of the many digital media that can be used as objects to insert messages or secret messages using methods Least Significant Bit (LBS) This method determines data by replacing the bits of data that at least means that it is closed with bits of confidential data. From this meode the author will combine with the Quick Response Code (QR), in order to produce encryption that has higher security, the result of embedding the cover image into a stgno image, will be encrypted again to Quick Response Code (QR).