Novel Secure Hybrid Image Steganography Technique Based on Pattern Matching

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.

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.

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.

Addition of hash component in a message is always for verification of authentication of message without integrity. In order to retain integrity certain schemes such as Merkle–Damgard scheme or Rabin scheme based on the block cipher can be used. However, the block cipher schemes in messages do not get applicable on image which are encoding message in a visual format. Therefore, block cipher based schemes are not able to provide tamper localization in case of image authentication. Tamper detection is needed in case of images as it is not visualized without proper verification. Moreover, localization is not possible by hash verification making the authentication processes only detectable but not identifiable. The paper presents a generation process of three least significant bits of hash function. The image insertion is not visualized due to human eye limitation. The method proposed is able to embed a secret image (gray scale) inside a corner image. Experimental results show an improvement in peak signal-to-noise ratio (PSNR) values of the proposed technique over the other techniques available, such as hash-based LSB(2-3-3) image steganography in spatial domain. This paper proposes an image authentication process not only for robustness, security, and tamper detection but also successfully able to identify tamper by a process of tamper localization. The parameters compared include the classical mechanism along with newly introduced entropy measurement of images. A performance analysis is able to show the result claimed in the paper. The paper uses a least significant bit (LSB) based hash function, which is a blind technique as image-related information is never sent to receiver separately. In fact, the proposed approach is a clever design as the generated hash function will be embedded in the image itself. The proposed mechanism is able to offer good imperceptibility between original image and embedded image with hash bits. Even a minute tampering can be detected with proper localization; the localization of tampering is having its wide applicability in case of forensic evidence of malicious image morphing.

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

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.

WITHDRAWN: Contrasting the performance metrics of discrete transformations on digital image steganography using artificial intelligence

Image steganography conceals secret information in a cover image .It is used for secure data transfer. Various LSB (least significant bits) approaches have been used over the years in steganography. This paper proposes a novel technique to improve the conventional LSB technique for image steganography by using pseudo random number generation using Henon chaotic map. The random numbers are used to encrypt the hide image which is embedded in the cover picture. This encryption using pseudo random generator provides sufficient security to the payload as the same set of random numbers cannot be regenerated without knowing the exact random generator function and thus the secret data cannot be retrieved easily. The proposed technique has been tested successfully on various .jpg files and corresponding PSNR values have been calculated.

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.

This paper introduces a best approach for Least Significant Bit (LSB) based on image steganography that enhances the existing LSB substitution techniques to improve the security level of hidden information. It is a new approach to substitute LSB of RGB true color image. The new security conception hides secret information within the LSB of image where a secret key encrypts the hidden information to protect it from unauthorized users. In general, in LSB methods, hidden information is stored into a specific position of LSB of image. For this reason, knowing the retrieval methods, anyone can extract the hidden information. In our paper, hidden information is stored into different position of LSB of image depending on the secret key. As a result, it is difficult to extract the hidden information knowing the retrieval methods. We have used the Peak Signal-to-Noise Ratio (PSNR) to measure the quality of the stego images. The value of PSNR gives better result because our proposed method changes very small number of bits of the image. The obtained results show that the proposed method results in LSB based image steganography using secret key which provides good security issue and PSNR value than general LSB based image steganography methods.

In day-to-day life, information plays a major role. The value of those information becomes higher. So, we need to protect the information from intruders who try to get the secret information. In protecting those information, data compression deals a lot. Compression techniques are of two types which includes lossy and lossless compression. Steganography is the process which is used to protect the information by encrypting the compressed image with secret data and then extract the secret data from the compressed image by decryption. This paper utilizes an reversible data hiding (RDH) algorithm to boost the efficiency of encryption and decryption of the cover image by implementing the steganographic technique. RDH helps to accomplish the reason for picture content security. The encrypted data has been embedded within the cover image using the least significant bit (LSB). The proposed model has been evaluated based on criteria like savings percentage (SP%), compression time (CT), compression ratio (CR), mean squared error (MSE), and peak signal-to-noise ratio (PSNR). In comparison to previous systems that use the RSA algorithm, this technique has improved performance and system methodology.

Background and Objective: The public and group communication carried out in the social, cloud, and mobile networks suffer from unauthorized users. The data security is required for secure authentication, monetary transactions and other sensitive information. The steganography methods empower the user with invulnerable communication in public domain. In this paper, a region secure and pattern based alternate 2B-3C (2Bit-3Channel) Steganography method is proposed to improve the content reliability and data security. Methods: In this method, the cover pixels are retrieved by applying the spiral rectangular pattern over the cover image. This spiral pattern also secures the core content region and the pixels from the core ROI (Region of Interest) is used as a cover only for larger size secret information. In this proposed steganography method, two channels are considered alternatively based on the defined rules. The LSB (Least Significant Bit) of both channels is XOR with input data bits and key to perform data hiding. The method is applied on real time color images taken from COREL and USC-SIPI-ID. The evaluation of proposed steganography approach is done using MSE (Mean Square Error), PSNR (Peak Signal-to-Noise Ratio), BER (Bit Error Rate), NCC (Normalized Cross Correlation) and SSIM (Structural Similarity Index Matrix). Result: The comparative results are generated for 50 real time images against the existing LSB (Least Significant Bit), LSBM (Least Significant Bit Modulation), LSBMR (Least Significant bit Matched Revisited), SCC (Stego Color Cycle), SHSI (Simple Hue-Saturation-Intensity), HIS-MLSB(Simple Hue-Saturation-Intensity-Modified LSB) and IMMEA(Iterative Magic Matrix Encryption Algorithm) methods. Conclusion: The experimentation results verified that the proposed 2B-3C approach improved the data hiding in qualitative and quantitative aspects.

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

Many steganographic schemes based on popular least significant bit (LSB) embedding have been proposed. The embedding procedure is totally independent of pixel values due to the fact that only the LSB has to be altered. Other methods either randomly increment/decrement the pixel value or use a function to do so. Because of this, the maximum embedding capacity cannot exceed 1 bit per pixel (bpp). State-of-the-art steganographic schemes, such as edge adaptive (EA) and highly undetectable stego (HUGO), aim at such LSB-based approaches with the help of LSB-matching algorithms and, unlike classical steganography, are more concerned about the undetectability level of the stego image rather than the peak signal-to-noise ratio (PSNR) of the stego images. There is a trade-off between detectability and the embedding rate of the stego images. The larger the embedding rate, the higher the chance of detectability, and the opposite is also true. On the other hand, classical steganographic approaches aim for maximum embedding capacity (say 4 bpp) while their main ability is to provide greater PSNR values rather than undetectability. In this work, a novel modular steganographic scheme is proposed in a spatial domain that takes advantage of error images resulting from applying an image quality factor (the same as the ones used in JPEG compression) in order to find the pixels where the secret data could be embedded. We show that our proposed method is less detectable compared to the EA method. The proposed method is almost as undetectable as HUGO. The detectability level is evaluated by the most recent state-of-the-art steganalysis attack, called ensemble classifiers, with second-order subtractive pixel adjacency model features given as their input. In addition, the proposed method can embed up to 4 bpp, yet maintain a high PSNR value.

A secure image steganography algorithm based on least significant bit and integer wavelet transform