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This work presents a new method of data hiding in digital images, in discrete cosine transform domain. The proposed method uses the least significant bits of the medium frequency components of the cover image for hiding the secret information, while the low and high frequency coefficients are kept unaltered. The unaltered low frequency DCT coeffici...
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... secret message is hidden in more than one cover image. While in the case of small size of secret message some coefficients are left unaffected. The proposed algorithm of data hiding has the property of reversibility and hidden message is recovered in its full strength. The secret message recovered from a stego image of 8 bits hiding is shown in Fig. 6. The resultant hiding capacity, M SE, P SN R and M SSIM for a different number of LSB substitution are listed in Tab. 1. The results shown in Tab. 1 reveals that the hiding capacity and M SE increases with increasing the number of bits used for data hiding, while the P N SR and M SSIM decreases with increasing the number of hiding bits ...
Context 2
... secret message is hidden in more than one cover image. While in the case of small size of secret message some coefficients are left unaffected. The proposed algorithm of data hiding has the property of reversibility and hidden message is recovered in its full strength. The secret message recovered from a stego image of 8 bits hiding is shown in Fig. 6. The resultant hiding capacity, M SE, P SN R and M SSIM for a different number of LSB substitution are listed in Tab. 1. The results shown in Tab. 1 reveals that the hiding capacity and M SE increases with increasing the number of bits used for data hiding, while the P N SR and M SSIM decreases with increasing the number of hiding bits ...
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Abstract As a large number of images are transmitted through social networks every moment, terrorists may hide data into images to convey secret data. Various types of images are mixed up in the social networks, and it is difficult for the servers of social networks to detect whether the images are clean. To prevent the illegal communication, this...
Citations
... Digital watermark -Fast-DCT, a decomposition of 2D-DCT into a pair of 1D-DCTs -Low capacity, a digital watermark embedded in a digital image is relatively small [42] 2018 Binary sequence data -Based on DCT and Latent Dirichlet Allocation (LDA) classification, a secret data is transformed to a binary sequence and segmented, then the image whose feature sequence matches the secret data segments is selected as the cover image -Low capacity per one cover image [47] 2019 Image -Medium frequency coefficients of DCT are subjected to LSB substitution -Low capacity [21] 2021 Text -Transformed the cover image and text message from spatial domain to frequency domain using DCT and buried the text message using redundant bits in the cover image -Low capacity [9] Content courtesy of Springer Nature, terms of use apply. Rights reserved. ...
... Our experiment implements and compares the three existing methods [5,21,28] with our four algorithms presented in Section 3. The comparison is chosen based on the most recent and relevant works whose goals are most similar to those of our own. The cover images used in the experiment are chest X-Rays in patients with Pneumonia which are available for download on Kaggle [25] (see Fig. 11). ...
... The results for the root mean square error (RMSE) are shown in Table 4. All four proposed methods have smaller RMSEs than the prior work [21], and our RMSEs are only one digit. ...
Several medical consultations and examinations have been undertaken online since the Covid outbreak. However, when private data was communicated over the internet or uploaded to the cloud, medical information became more susceptible to security risks. Steganography is a technique that can be used to hide sensitive information within a cover image. This paper presents four improved algorithms to enhance steganography's performance in medical images. A full-size hidden image that is as huge as a cover image cannot be handled by previous methods, which is what the algorithmic design is meant to address. Several creative methods are presented, including the computation of Discrete Cosine Transform (DCT) coefficients based on scaled floating values, the addition of an adaptive compression matrix, and a new approach for systematically dispersing a concealed number of bits across multiple separate locations in the cover image. The results of the experiment showed a notable advancement over the earlier research. Our secret image size is substantially larger than the past studies, yet the structure similarity index matrix (SSIM) of the best reconstructed secret image is close to ideal, the peak signal-to-noise ratio (PSNR) and the payload capacity are higher than in the previous studies. This research is beneficial since it contributes to a medical application for enhancing the security of information concealed in chest X-ray images. Medical personnel can generate an image that conceals patient information in a secure manner.
... These methods usually use fewer coefficients for embedding and, consequently, embedding capacity is reduced. For instance, in [24], low-and high-frequency DCT coefficients are not changed and the embedding in LSB of medium frequency DCT coefficients is proposed. Keeping the low-frequency coefficients constant, maintains the quality of the uniform areas of the cover image, while by keeping the high-frequency coefficients constant, the quality of the edges of the cover image is maintained. ...
... There are different criteria for comparing steganography methods, which can be divided into three main categories; stego image quality, embedding capacity, and attack resistance. In addition to GA-Shield (our proposed method), other methods used for the comparison are Jsteg (as a basic method in the field of DCT), GPM1 [47] (as a GA-based method in the field of DCT), Shield [6] (as an adaptive multi-bit embedding method in the DCT coefficients), and three newer methods including DCT-M3 [4], MPS [39], MedFreq [24] and ADCT_LC [37]. The test results provided for all methods are the average of 200 test images via http://lear.inrialpes.fr, ...
... Examination of the presented results in Table 8 showed that the DCT-M3 [4] method had the lowest capacity, while the MedFreq [24] had the highest capacity. This outcome, based on their embedding algorithm, was expected though. ...
Steganography is an appropriate approach to establish a secure connection between the sender and the receiver. Data embedding in Discrete Cosine Transform (DCT) coefficients for JPEG images is one of the most practical approaches nowadays. In this paper, a new method called GA-Shield is proposed, in which, instead of using fixed embedding capacity, embedding a different number of bits in the quantized DCT coefficients according to the magnitude of the coefficient is used to spread bits of secret message in the most suitable coefficients. In addition, this method uses a genetic algorithm to minimize the distortion due to embedding. This minimization is performed by deciding on the best formula to calculate coefficient value after embedding. In this phase, PSNR is used as the metric to measure the amount of distortion in the cover image to produce the stego image. As these changes decrease, the value of PSNR would be optimized, and the stego image would have better quality. The proposed method can embed 300 to 20,000 bits of data (on average) in the cover image and produce the stego image with a PSNR value in the range of 65 to 40 and a SSIM value of more than 0.985. The consequences of comparisons with the state-of-the-art show that despite the fact that the proposed technique has less embedding capacity than some of the current ones, the superiority of stego image quality and security of the proposed technique, mainly at low embedding levels, is significant.
... The interdependencies among the coefficient are removed to gain insight into the image details such as edges, energy, ... etc. It also makes the separation of the high energy coefficients from the rest of the coefficients very easy [43]. ...
This work presents a new asymmetric data hiding technique that hides a variable number of secret message bits in the discrete cosine transform (DCT) coefficients of a cover image using a modular distance technique. Prior to data hiding, the proposed framework transforms a cover image from a spatial domain to various frequency coefficients using DCT. The DCT coefficients are arranged in two groups: one with low-frequency coefficient, and the other with the medium and high-frequency coefficients.~The~medium and higher frequency coefficients are processed for variable data hiding asymmetrically.~The~proposed technique hides variable sets of secret information bits in different coefficients. The~variation in hidden secret information is maintained using a key developed based on the modulo of distance of a coefficient from the reference point. The same key is also used to retrieve the confidential information at the receiver ends.~The results reveal that the presented framework does not create any visually significant distortion, and thus the hidden information does not attract the human visual system (HVS). The~technique also results in high data hiding efficiency.
Adversarial examples are samples that are close to benign samples with respect to a distance metric, but misclassified by a neural network. While adversarial perturbations of images are usually computed for RGB images, we propose perturbing straight on JPEG coefficients with the ability to individually control the perturbation applied on each color channel and frequency. We find that perturbation as a function of perceptual distance is most efficient for medium frequencies, especially when JPEG compression is used in defense. Overall, we show that attacks on JPEG coefficients are more efficient than state-of-the-art methods that (mainly) apply their perturbation in RGB pixel space. This is partly due to the use of the YCbCr color space, which allows to perturb luma information exclusively, but also due to perturbing the cosine transform coefficients instead of pixels. Moreover, adversarial training using such JPEG attacks with various frequency weighting vectors results in generally strong robustness against RGB and YCbCr attacks as well.
