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We propose a new steganography method to hide an image into another image using matrix multiplication operations on max-plus algebra. This is especially interesting because the matrix used in encoding or information disguises generally has an inverse, whereas matrix multiplication operations in max-plus algebra do not have an inverse. The advantage...
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In this paper, we present a novel image steganography method which is based on color palette transformation in color space. Most of the existing image steganography methods modify separate image pixels, and random noise appears in the image. By proposing a method, which changes the color palette of the image (all pixels of the same color will be ch...
Steganography algorithms aim to hide secret messages in a cover medium to provide imperceptibility to an attacker. Despite becoming the preferred technique for data hiding, the K-bit least significant bit (LSB) provides high variability and negatively impacts the visual quality of the cover image. Thus, optimization algorithms have been proposed to...
![Figure 1. Basic components of secure steganography system [11].](profile/Waoud-Majid/publication/327701226/figure/fig1/AS:671908328640513@1537206837145/Basic-components-of-secure-steganography-system-11_Q320.jpg)
![Figure 2. The main components of the BPIS algorithm [11].](profile/Waoud-Majid/publication/327701226/figure/fig2/AS:671908328644609@1537206837175/The-main-components-of-the-BPIS-algorithm-11_Q320.jpg)
Recently, a new secure steganography algorithm has been proposed, namely, the secure Block Permutation
Image Steganography (BPIS) algorithm. The new algorithm consists of five main steps, these are: convert
the secret message to a binary sequence, divide the binary sequence into blocks, permute each block using
a key-based randomly generated permut...
Image steganography is used to hide a secret image inside a cover image in plain sight. Traditionally, the secret data is converted into binary bits and the cover image is manipulated statistically to embed the secret binary bits. Overloading the cover image may lead to distortions and the secret information may become visible. Hence the hiding cap...
Least Significant Bit replacement, a spatial domain algorithm, is the most popular and widely used technique in image steganography due to its simplicity and effectiveness. Different methods of data hiding in spatial domain have been proposed and continue to be improved upon. Among them, the LSB replacement method is quite simple and the most popul...
Citations
... The Steganography Modified Least Significant Bit using the Columnar Transposition Cipher and Caesar Cipher Algorithm has been widely used to solve various problems such as, insert text to an image [5], png image security [6], secure the image file [7], image hiding [8], hiding and data safety [9]. There are also study in using another steganography method, such as Max-Plus Algebra, to implement an image based steganography as proposed in [10]. ...
Steganography technique is a technique to hide data or information into other media such as digital images, text, sound, or video. One of the simplest methods of Steganography in the concept of Steganography is the Least Significant Bit. The Least Significant Bit (LSB) method hides the message by inserting the message at the lower or rightmost bits in the cover work file as a medium to hide the message. Caesar Cipher is one method that replaces each letter in the plaintext with letters that are at odds with certain numbers in the alphabet. Columnar transposition Cipher is one method in which messages are written in rows of a specified length, then are read column by column in the order of reading based on a keyword. The message is inserted into the cover image with the target pixel determination to be inserted based on the results of the Caesar Cipher process of the Columnar Transposition Cipher index to the random value of the Multiply With Carry Generator algorithm. The system implementation uses the C# programming language. The results of this study indicate that the implementation of a combination of Caesar Cipher, Columnar Transposition Cipher, and Multiply With Carry Generator can maintain the confidentiality, integrity, and security of data.
... But the calculations time is not suitable for applying on the fog environment. In Kiswara et al. (2018)authors develop a steganography method using matrix multiplication; this method achieves an advantage which is that the size of the image that can be hidden into the cover image can be the same size of the cover image; this method has an accepted level of strength but there are not keys used in the embedding process and consumed time has not been considered. Another hybrid strategy developed in Syed et al. (2018)based on data encryption standard (DES) for cryptography and LSB for steganography; DES has high computational cost especially when dealing with large data capacity and LSB is traditional and popular to be used nowadays. ...
Fog computing has become a fast intermediate between the cloud and the internet of things (IOT) devices. So, the communication channel between the fog and IOT devices must be secured against attacks. Both Cryptography and steganography are well-known techniques for data security. Each of them has its own advantages and strength points, hence, combining Cryptography and steganography in a hybrid system certainly promotes the system’s level of security. Although several hybrid security strategies have been proposed, they suffer from many drawbacks especially when they are applied in fog environments. Fog computing requires not only high security level but also a real time transmission. Hence, recent hybrid security strategies cannot be applied directly in fog environments as they suffer from long processing time. This paper introduces a new Fog Based Security Strategy (FBS²). FBS² is a hybrid security strategy as it combines Cryptography and steganography techniques. The proposed Cryptography Technique (PCT) is divided into two phases, namely; confusion and diffusion. The former scrambles the secret image pixels, while the latter changes the pixels values using new confusion and diffusion methodologies respectively. Confusion divides the secret images into closed loops of pixels, then rearrange the pixels into straight paths, while diffusion employs a Programmable Linear Feedback Shift Register (PLFSR). On the other hand, the Proposed Steganography Technique is implemented using the discrete wavelet packet transform. Embedding process depends on a new matching procedure, which is based on the most significant bits of both the encrypted secret image and the corresponding employed cover image pixels. Least significant bits (LSBs) are used as indicators to the matching process. At first an intermediate code is derived from the matching process, then, it is encrypted to represent the LSBs of the stego-image. Experimental results have shown that the proposed FBS² outperforms the previous counterparts in terms of efficiency, security, and processing time, which proves its suitability for application on the fog.
... Max-plus algebra is used in machine scheduling, telecommunication networks, control theory, manufacturing systems, parallel processing systems, and traffic control [5][6][7]. Max-plus algebra is also used in image steganography [8]. Max-plus algebra can be used to model disk events related to synchronization and time delays [9]. ...
In this paper, we consider the eigenproblems for Latin squares in a bipartite min-max-plus system. The focus is upon developing a new algorithm to compute the eigenvalue and eigenvectors (trivial and non-trivial) for Latin squares in a bipartite min-max-plus system. We illustrate the algorithm using some examples. The proposed algorithm is implemented in MATLAB, using max-plus algebra toolbox. Computationally speaking, our algorithm has a clear advantage over the power algorithm presented by Subiono and van der Woude. Because our algorithm takes 0 . 088783 sec to solve the eigenvalue problem for Latin square presented in Example 2, while the compared one takes 1 . 718662 sec for the same problem. Furthermore, a time complexity comparison is presented, which reveals that the proposed algorithm is less time consuming when compared with some of the existing algorithms.
... This technique has achieved a better security for their secret images [25]. Additionally, the improved security in steganography was achieved by using affine transformation in the integer DCT coefficients of the stego-media [26]. ...
Network security is the most essential aspect of information technology among today’s emerging digital technologies which demands secured communication of information. In this digital network, it is essential to secure the data from intruders and unauthorized receivers. Steganography plays a vital role in secure transmission of data. This paper proposes a steganography method to hide data using affine transformation technique. The secret data are embedded in the coefficients of integer wavelet transform of the video frames. While embedding, the pixel values are distributed using affine transformation. The proposed method has been tested on many input data and the performance is evaluated both quantitatively and qualitatively. The results indicate the enhanced capability of the proposed method that can ensure imperceptible distortions with minimum computational cost in terms of PSNR factor over the existing methods.
... But the calculations time is not suitable for applying on the fog environment. In Kiswara et al. (2018)authors develop a steganography method using matrix multiplication; this method achieves an advantage which is that the size of the image that can be hidden into the cover image can be the same size of the cover image; this method has an accepted level of strength but there are not keys used in the embedding process and consumed time has not been considered. Another hybrid strategy developed in Syed et al. (2018)based on data encryption standard (DES) for cryptography and LSB for steganography; DES has high computational cost especially when dealing with large data capacity and LSB is traditional and popular to be used nowadays. ...
... The pixel of an image can be converted into 8 bit (binary digit). The first bit to fourth bit is called LSB or Least Significant Bit because the bit value that changed in this position doesn't have impact on the image [5]. The fifth bit to eighth bit is called MSB or Most Significant Bit, because the bit value that changed in this position will give an effect to the image. ...
... Max-plus algebra is also used in image steganography [9]. In [10], the author has described the whole Dutch railway system by a max-plus system. ...
In this paper, we consider the eigenproblems for Latin squares in a bipartite min-max-plus system. The focus is upon developing a new algorithm to compute the eigenvalue and eigenvectors (trivial and non-trivial) for Latin squares in a bipartite min-max-plus system. We illustrate the algorithm using some examples. Furthermore, we compare the results of our algorithm with some of the existing algorithms which shows that the propose method is more efficient.
... Max-plus algebra can be used to model disk events related to synchronization and time delays [6]. A new steganography method has been proposed to hide an image into another image using matrix multiplication operations on max-plus algebra [7]. In [8] the author has shown how max-plus algebra can be helpful for the dynamic programming of algorithms. ...
The eigenproblem for matrices in max-plus algebra describes the steady state of the system, and therefore it has been intensively studied by many authors. In this paper, we propose an algorithm to compute the eigenvalue and the corresponding eigenvectors of a square matrix in an iterative way. The algorithm is extended to compute the nontrivial eigenvectors for Latin squares in max-plus algebra.
A square array whose all rows and columns are different permutations of the same length over the same symbol set is known as a Latin square. A Latin square may or may not be symmetric. For classification and enumeration purposes, symmetric, non-symmetric, conjugate symmetric, and totally symmetric Latin squares play vital roles. This article discusses the Eigenproblem of non-symmetric Latin squares in well known max-plus algebra. By defining a certain vector corresponding to each cycle of a permutation of the Latin square, we characterize and find the Eigenvalue as well as the possible Eigenvectors.
