Adaptive Steganography Scheme Using More Surrounding Pixels (original) (raw)
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Steganography Using More Surronding Pixels
—Nowadays among the steganography techniques and particularly in conventional least significant bit (LSB) insertion method, there is a challenging issue and that is how to embed the secret bits in a medium like a typical 8-bit gray scale image in a way to be hidden to the human vision system. The gray scale image is called Cover Image and the pixels that carry the secret bits are called Target Pixels. The considerable point is how the capacity of every target pixel is achieved in order to maintain an acceptable imperceptibility of the secret data. The number of bits embedded in each target pixel is called Capacity. Some methods utilize either three or four adjacent neighbors of a target pixel so as to find its capacity such as BPCS, PVD and MBNS. In this paper, a method is proposed that uses at least four numbers of eight surrounding pixels of a target pixel. The more pixels are used for estimating the capacity, the higher image quality is achieved and vice versa. Thanks to this fact, smaller image's distortion is made in the cover image. The method is called MSPU that stands for more surrounding pixels using.
International journal of Computer Networks & Communications
Steganography is a vital technique for transferring confidential information via an insecure network. In addition, digital images are used as a cover to communicate sensitive information. The Least Significant Bit (LSB) method is one of the simplest ways to insert secret data into a cover image. In this paper, the secret text is compressed twice by an Arithmetic coding algorithm, and the resulting secret bits are hidden in the cover pixels of the image corresponding to the pixels of each of the following three methods, one of three methods is used in each experiment: The first method, the edges of the image are modified to increase the number of edges, in the second method the lighter-colored regions are selected, and in the third method, the two methods are combined together to increase security and keep the secret message unrecognized. Hiding in each of the previous methods is done by using the LSB technique in the last 2-bit. The correction approach is used to increase the stego ...
On the Information Hiding Technique Using Least Significant Bits Steganography
Steganography is the art and science of hiding data or the practice of concealing a message, image, or file within another message, image, or file. Steganography is often combined with cryptography so that even if the message is discovered it cannot be read. It is mainly used to maintain private data and/or secure confidential data from misused through unauthorized person. In contemporary terms, Steganography has evolved into a digital strategy of hiding a file in some form of multimedia, such as an image, an audio file or even a video file. This paper presents a simple Steganography method for encoding extra information in an image by making small modifications to its pixels. The proposed method focuses on one particular popular technique, Least Significant Bit (LSB) Embedding. The paper uses the (LSB) to embed a message into an image with 24-bit (i.e. 3 bytes) color pixels. The paper uses the (LSB) of every pixel’s bytes. The paper show that using three bits from every pixel is robust and the amount of change in the image will be minimal and indiscernible to the human eye. For more protection to the message bits a Stego-Key has been used to permute the message bits before embedding it. A software tool that employ steganography to hide data inside of other files (encoding) as well as software to detect such hidden files (decoding) has been developed and presented. https://sites.google.com/site/ijcsis/
An enhanced Least Significant Bit Steganographic Method for Information Hiding
Journal of Information Engineering and Applications, 2012
The least significant bit (LSB) insertion method is a simple steganographic algorithm that takes the least significant bit in some bytes of the cover medium and swaps them with a sequence of bytes containing the secret data in order to conceal the information in the cover medium. However its imperceptibility and hiding capacity are relatively low. This is as revealed by the statistical characteristics of its resultant stego images compared to the original cover images. To increase the level of imperceptibility and the hiding capacity in the LSB insertion method, this research proposes an enhanced LSB method that employs a selective and randomized approach in picking specific number of target image bits to swap with the secret data bits during the embedding process. To facilitate the selective picking of the target image bits, the standard minimal linear congruential number generator (LCG) is used. The message digest (digital signature) of a user supplied password is used to seed the LCG and to extract the message from the cover medium. In measuring the effectiveness of the proposed method, the study adopted an experimental research design where the statistical characteristics of the proposed method stego images were compared with those of the traditional LSB method in a comparative experiment designed to establish the levels of image distortion (noise) introduced in the original cover image when either of the methods is used under the same payload and image. The experiment results indicated improved levels of imperceptibility and hiding capacity in the proposed method.
An efficient steganographic technique for hiding data
Journal of the Egyptian Mathematical Society, 2019
Steganography is the technique for hiding data and aims to hide data in such a way that any eavesdropper cannot observe any changes in the original media. The least significant bit (LSB) is one of the most public techniques in steganography. The classical technique is LSB substitution. The main idea of this technique is to directly alter some LSB of the cover image with the secret data. The essential drawback of the available LSB techniques is that increasing the capacity of the stego image leads to decreasing its quality. Therefore, the goal of the proposed method is to enhance the capacity taking high visual quality into consideration. To achieve this goal, some LSB of the cover image are inverted depending on the secret data for embedding instead of replacing LSB with the secret data. First, the maximum and minimum values in the secret data are determined then subtract all values of the secret data from this maximum value. Finally, make a division for the results and embed the new results into the cover image to obtain the stego image. The results show that the proposed method gives high capacity and good imperceptibility in comparison with the previous methods.
Robust Increased Capacity Image Steganographic Scheme
International Journal of Advanced Computer Science and Applications, 2014
with the rising tempo of unconventional right to use and hit protection of secret information is of extreme value. With the rising tempo of unconventional right to use and hit, protection of secret information is of extreme value. Steganography is the vital matter in information hiding. Steganography refers to the technology of hiding data into digital media without depiction of any misgiving. Lot of techniques has been projected during past years. In this paper, a new steganography approach for hiding data in digital images is presented with a special feature that it increases the capacity of hiding data in digital images with the least change in images perceptual appearance and statistical properties at too much less level which will be very difficult to detect.
A High Capacity Data-Hiding Technique Using Steganography
2013
Steganography techniques were introduced and developed with the purpose to provide vast array of methods for secure communication. In this work, we present a new LSB-based steganography technique to embed a secret image in a cover image while keeping the perceptual degradation of the cover image to a minimum level so as to avoid visual attacks. To achieve high embedding capacity we propose to use the YIQ color space model and RGBA based cover image. RGB value's of the secret image pixel's is first converted into YIQ color space, which are then embedded into the least significant bits of the color pixel's of the cover image, as well as in the alpha channel. Results obtained demonstrate that it is practically possible to hide an image in another image while maintaining acceptable image quality.
A Development of Least Significant Bit Steganography Technique
Iraqi Journal of Computers, Communication and Control & System Engineering (IJCCCE), 2020
Recently, the world has been interested in transferring data between different devices. The transmission of data must be encrypted so that the intended receiver can only read and process a secret message. Hence, the security of information has become more important than earlier. This paper proposes the least significant bit Steganography method to hide a secret message inside an image cover via using dynamic stego-key. To check the effectiveness of the proposed method, many factors are used for evaluation and compared with another method. The results illustrate more robustness at steganography since stego-key depends on the cover image to hide a secret message.
This paper presents a novel technique for improved data embedding in cover images based on least significant bit and pixel-value differencing. The proposed method is based on the properties of human visual system i.e. eyes can tolerate larger changes in edge areas as compared to smooth areas. Therefore, the method utilizes the HVS concept and hides large amount of secret data in edge areas while less amount of data in smooth areas. The results of the proposed method are verified using extensive simulations.
Image feature based high capacity steganographic algorithm
Multimedia Tools and Applications, 2019
Steganography is the growing field of research, where hiding techniques are used to secure the communicative elements (e.g., images). In this paper, the message is hidden in the color image in special domain, exploring multi-bit Least Significant Bit (mLSB) steganography which again increases the scope to capacitate more bits hence increases the capacity. Path trace, based on eccentricity of pixels gives the potential pixels i.e., sampled pixels which lowers the probability of identifying the embedding location. Perspective based technique and meticulous statistical analysis are applied to immune the algorithm from sterilization along with other attacks. The algorithm overcome different tests done by benchmark like StirMark, Receiver Operating Characteristic (ROC) curve, steganalysis and statistical tools. The algorithm also ensures insignificant visual disturbance/distortion.