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Transform-based techniques partially address challenges like robustness and the imperceptibility in image steganography. Such approaches, however, increase the memory requirement and reduce the quality of the cover image and hiding capacity. Moreover, the steganography is always coupled with cryptography to strengthen the confidentiality. This pape...
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Citations
... However, this scheme achieved a hiding capacity of 25% of the cover image and an SNR of 44.6 dB [24]. In 2018, Shafi et al. proposed an image steganography technique based on fuzzy wavelet and DWT, which they tested by embedding text within an image [25]. Finally, in 2019, Sharifzadeh et al. proposed a CNN-MLP-based classifier for image classification, combining the positive features of a convolutional neural network (CNN) and multilayer perceptron (MLP) to enhance image detection capabilities [26]. ...
Steganography is a widely used technique for concealing confidential data within images, videos, and audio. However, using text for steganography has not been sufficiently explored. Text-based steganography has the advantage of a low bandwidth overhead, making it a promising alternative for protecting sensitive information. Among languages, Arabic is known for its linguistic richness, making it ideal for text-based steganography. This paper proposes a robust, dynamic, and multi-layered steganography approach that uses text, encryption algorithms, and images. This approach utilizes Arabic diacritic features to hide limited-size and highly classified information. The algorithm uses several scenarios and is extensively tested to ensure the required level of security and user performance. The experimental results on actual data demonstrate the robustness of the proposed algorithm, with no noticeable impact on the carrier message (original text). Furthermore, no known potential attack can break the proposed algorithm, making it a promising solution for text-based steganography.
... dB An adaptive hybrid fuzzy-wavelet approach for image steganography using bit reduction and pixel adjustment. [13] 36.26 dB A Secure Spatial Domain Image Steganography u sing Genetic Algorithm and Linear Congenital Generator. [14] 53.40 dB 52.49 ...
The ever-increasing development of telecommunications has made secure transmission one of the most important issues today. Using steganography keeps information away from unauthorized people, and the information is hidden inside the original file without harming the marks. Since there is a high hiding capacity in the image, the use of image steganography is much more common than other steganography methods. In this article, the wavelet transform steganography technique is used, and the comparison results of the images before and after applying steganography, as well as the histogram output, show that this method benefits from high resistance, as well as the SNR of this method compared to other methods. The reviewed results show the superiority of this steganography method.
... The purpose was to improve the accuracy level in design and reduce the maintenance cost as well as losses. ANnets are used in many different fields such as signal processing [46], feature extraction [47] and optimization [48]. As shown in Figure 1, the structure proposed in this study is a fully connected feedforward back propagation neural network (FFBPN-net). ...
The precise prediction of power estimates of wind–solar renewable energy sources becomes challenging due to their intermittent nature and difference in intensity between day and night. Machine-learning algorithms are non-linear mapping functions to approximate any given function from known input–output pairs and can be used for this purpose. This paper presents an artificial neural network (ANN)-based method to predict hybrid wind–solar resources and estimate power generation by correlating wind speed and solar radiation for real-time data. The proposed ANN allows optimization of the hybrid system’s operation by efficient wind and solar energy production estimation for a given set of weather conditions. The proposed model uses temperature, humidity, air pressure, solar radiation, optimum angle, and target values of known wind speeds, solar radiation, and optimum angle. A normalization function to narrow the error distribution and an iterative method with the Levenberg–Marquardt training function is used to reduce error. The experimental results show the effectiveness of the proposed approach against the existing wind, solar, or wind–solar estimation methods. It is envisaged that such an intelligent yet simplified method for predicting wind speed, solar radiation, and optimum angle, and designing wind–solar hybrid systems can improve the accuracy and efficiency of renewable energy generation.
... As suggested by Setiadi (2020) that SSIM is a better measure of imperceptibility in all aspects, Table 7 presents the values obtained for SSIM, NCC and BER for the stego images of size (512 × 512) under considered image databases. SSIM is another tool to assess the imperceptibility of the image. ...
Secret communication of sensitive data must progress in a trustworthy environment through data hiding. Using Mamdani fuzzy logic to identify color proximity at the block level and a shared secret key and post-processing system, this paper attempts to develop a robust data hiding scheme with similarity measures to ensure good visual quality, robustness, imperceptibility and enhance the security. In accordance with the Gestalt principle, proximity among the nearby objects is higher, whose value varies from expert to expert. Therefore, a possibility for type-I fuzzy logic to be used to evaluate proximity. Fuzzy proximity is computed by means of a difference in intensity (colordiff) and distance (closeness). Further, the block color proximity obtained from the proximity calculation network is graded using an interval threshold. Accordingly, data embedding is processed in the sequence generated by the shared secret keys. The tampering coincidence problem is solved through a post-processing approach to increase the quality and accuracy of the recovered secret message. The experimental analysis, steganalysis and comparisons clearly illustrate the effectiveness of the proposed scheme in terms of visual quality, structural similarity, recoverability and robustness.
... Earlier LSB steganography research (Chandramouli and Memon, 2001;Sutaone and Khandare, 2008) focused solely on designing the device to maximise payload capability by using the majority of the cover image pixels. The research issue became more oriented after that, with the goal of developing sophisticated, robust LSB-based cryptography-steganography that can withstand such steganalysis attacks (Patel and Meena, 2016;Rajendran and Doraipandian, 2017;Shafi et al., 2018). Learning methods, for example, were used to optimise LSB substitution (Maity and Kundu, 2009;Dadgostar and Afsari, 2016). ...
In 2020, Ashraf et al. proposed an interval type-2 fuzzy logic based block similarity calculation using color proximity relations of neighboring pixels in a steganographic scheme. Their method works well for detecting similarity, but it has drawbacks in terms of visual quality, imperceptibility, security, and robustness. Using Mamdani fuzzy logic to identify color proximity at the block level, as well as a shared secret key and post-processing system, this paper attempts to develop a robust data hiding scheme with similarity measure to ensure good visual quality, robustness, imperceptibility, and enhance the security. Further, the block color proximity is graded using an interval threshold. Accordingly, data embedding is processed in the sequence generated by the shared secret keys. In order to increase the quality and accuracy of the recovered secret message, the tampering coincidence problem is solved through a post-processing approach. The experimental analysis, steganalysis and comparisons clearly illustrate the effectiveness of the proposed scheme in terms of visual quality, structural similarity, recoverability and robustness.
... Steganography is a method to transfer secret data embedded within cover data through a public communication channel such as the Internet. In this method, an attacker cannot extract the secret data from the cover data [7,8]. ere are three important parameters for evaluating a secret data communication technique, namely, capacity, robustness, and transparency. ...
... For example, for coefficient values (8,14,21), we obtain three values x i � 8, x i+1 � 14, x i+2 � 21. Now, by manipulating one bit in the coefficients, we obtain 7 different values (shown in Table 1). ...
... For example, for numbers (8,14,21,29) we obtain values x i � 8, x i+1 � 14, x i+2 � 21, and x i+3 � 29. Clearly, we can generate different values by increasing/decreasing each of these coefficients. ...
LSB matching revisited is an LSB-based approach for image steganography. This method is a type of coding to increase the capacity of steganography. In this method, two bits of the secret message are hidden in two pixels with only one change. But this method provides no idea for hiding a message with a large number of bits. In other words, this method works only for n=2, where n is the number of bits in a block of the secret message. In this paper, we propose an improved version of the LSB matching revisited approach, which works for n>2. The proposed scheme contains two phases including embedding and extracting the message. In the embedding phase, we first convert the secret message into a bit-stream, and then the bit-stream is divided into a set of blocks including n bits in each block. Then we choose 2n−1 pixels for hiding such n bits of the secret message. In the next step, we choose the operations needed to generate such a message. Finally, we perform the obtained operations over the coefficients to hide the secret message. The proposed approach needs fewer changes than LSB MR when n>2. The capacity of the proposed approach is 2n−1/2n−1−1×100% higher than the F5 method where this value for n>2 is bigger than 75%. For example, the capacity of our scheme is 75% higher than the capacity of F5 for n=3. The proposed method can be used in the first step of every steganography method to reduce the change in the stego image. Therefore, this method is a new coding method for steganography. Our experimental results using steganalysis show that using our method provides around 10% higher detection error for SRNet over two steganography schemes.
... Using adaptive techniques, the researchers tried to improve the imperceptibility of the stego-image which ultimately leads to better embedding efficiency and with high embedding capacity if the error rate is minimum at the retrieval time, then the chances of detection of secret data will be least. For this researcher's switched to machine learning algorithms [121] such as Support Vector Machine (SVM) [161], Genetic Algorithm (GA) [98,143], Fuzzy Logic [71,78,142], Neural Networks (NN) [4] etc. The machine learning algorithms has been used in image steganography either for finding the area for embedding or pre-processing of the cover or secret image to enhance the security. ...
Steganography and steganalysis is a relatively new-fangled scientific discipline in security systems and digital forensics, respectively, but one that has matured greatly over the past two decades. In any specialism of human endeavour, it is imperative to periodically pause and review the state of the discipline for what has been achieved till date. This article scrutinizes where the discipline of steganography and steganalysis at this point in time in context to the common user and new researchers in terms of current trends. Also, what has been accomplished in order to critically examine what has been done well and what ought to be done better. The state-of-the-art techniques for steganography and steganalysis (image and video) have been deliberated for the last 5 years literature. Further, the paper also takes stock the dataset and tools available for multimedia steganography and steganalysis with the examples where steganography has been used in real-life. It is a corpus of the author’s opinion and the viewpoints of different other researchers and practitioners, working in this discipline. Additionally, experiments were done using image steganography techniques to analyse the recent trends. This survey is intended to provide a complete guide for common people and new researchers and scholars approaching this field, sight on the existing and the future of steganography and steganalysis.
... The LSB's manipulation for IW may utilize encryption or encryption fewer methods forsecuring host information [24]. These LSB based IW schemes may incorporate randomly adaptive, X-BOXmapping, multi-channel permutation, data hiding using histogram enhancement and quantization [25,26], imagefile features, edges selection, bit inverting method, MQTT (Modified Quantized Table Technique), bit replacement,DCT (Discrete Cosine Transform) [27,28] coefficient alteration, etc., methods for the encryption of secretinformation [29]. On the contrary, MSB's based IW schemes may utilize encryption or encryption fewer methodsfor securing host information. ...
In this article, a new and improvised image watermarking (IW) technique on colored images is proposed to mitigate robustness and imperceptibility issues found often in the past presented schemes. Most schemes exhibit low robustness due to LSB’s (Least Significant Bit) and MSB’s (Most Significant Bit) based information hiding in the cover image. However, most of these IW schemes have low imperceptibility as the cover image distortion reveals to the attacker due to information hiding in MSB’s. Such IW schemes used to hide the secret message via MSBs and LSBs are susceptible to malicious intruder attacks which results in low robustness, whereas, the attacks on MSB’s have an impact of reduced imperceptibility. Therefore, this paper propounds a digital IW method named as 2D Otsu algorithm, which allows embedding of a grayscale image into a colored host in the wavelet domain. According to this algorithm, the host image is disintegrated into three color bands of blue, red, and green. Each band is divided into small patches leading to the calculation of entropy followed by finding of the threshold that is estimated by taking the average of entropies of all the patches. Wavelet representation of each patch with entropy less than the threshold is given by applying DWT (Discrete Wavelet Transform). Later, by decomposing gray-scale image into binary bits, secret information embedded by quantization technique into optimal wavelet coefficient blocks either encoding wavelet coefficient differences to 0-bits or 1-bits called MultiBit Encoding (MBE). The results obtained show that the imperceptibility and robustness of this proposed model are superior to other proposed watermarking models and this model gives better results than other models at the same payload.
... However, a hiding capacity of 25% of the cover image and SNR 44.6 dB has been achieved through the proposed scheme. Shafi et al. (2018) proposed image steganography based on fuzzy wavelet and IWT which was tested with text on an image. Sharifzadeh et al. (2019) proposed a CNN-MLP based classifier for image classification in which a hybrid model using positive features of Convolution neural network (CNN) and Multilayer perceptron (MLP) was implemented to obtain better image detection. ...
The assurance of secret data transmitted over the Internet and confining its access to explicit grouped information has become a significant security and protection issue. To hide the presence of such information, a robust and blind color image steganography algorithm, using fractal cover images, Singular Value Decomposition (SVD), Integer Wavelet Transform (IWT), and Discrete Wavelet Transform (DWT) is proposed in this paper. The proposed algorithm conceals the color secret image intelligently inside a fractal cover image thus creating a unique stego-image that is virtually a replica of the original cover image. The novelty of this proposed blind image hiding method lies in the fact that a small file size of a unique fractal image can be used to conceal a large amount of information payload. The fractal cover images can be implemented without debasing its quality to make the shrouded information sufficiently strong against image processing attacks. The algorithm possesses features like robustness, imperceptibility, security, and greater hiding capacity due to the application of fractal compression, DWT-SVD, and IWT-SVD hybrid transform schemes. The secret image is inserted in U and V components of the fractal cover with a scaling factor based on the HVS model and a stego-image with sufficiently large keyspace is created. Furthermore, the proposed work compares the performance analysis and security offered by IWT- SVD and DWT- SVD hybrid combinations for different fractal covers using certain metrics like PSNR (Peak Signal to Noise Ratio), MSE (Mean Square Error), SSIM (Structural Similarity Index), BRISQUE (Blind/ Reference less Image Spatial Quality Evaluator) score and Bits per pixel (BPP). The results prove that image degradation is very less (less than 0.6%) in the proposed algorithm even when the secret image file size is more than double the file size of the fractal cover image which also saves the bandwidth and storage requirements.
