Fusion of Watermarking and Steganography for Protecting Image Ownership

The use of digital images has become very common because of the rapid increase of the internet over time. Moving digital images over the internet is easy, but keeping ownership is complex, and serious issues have emerged. Forgery, fraud, and pirating of this content are rising. Different techniques used to protect images, like watermarking and steganography, but these methods are not enough toprotect. So, providing new techniques is essential for protecting image ownership. We have proposed a fusion method of steganography and watermarking in this work. First, the secret message is encoded within the original image using the LSB technique to obtain the stego image. Secondly, the watermarking process is applied on the stego image using text watermarking or image watermarking to provide stego-watermarked-image. The proposed fusion watermarking and steganography method is very useful for protecting image ownership over insecure communication channels. An attacker cannot get the desired watermarked image from the stego-watermarked-image without knowing the secret message hiding inside it using the LSB technique. The proposed method is efficient, simple and secure; it provides significant protection for image ownership.

PENGGUNAAN CITRA HIMPUNAN JULIA SEBAGAI CITRA SAMPUL UNTUK MENYEMBUNYIKAN CITRA RAHASIA

Steganografi dengan metode fraktal (fractal steganography) adalah teknik menyembunyikan informasi atau pesan, yang dapat berupa citra rahasia, dalam suatu citra sampul (cover image) yang berupa citra fraktal (fractal image). Dalam penelitian ini digunakan citra fraktal matematis yaitu citra himpunan Julia dari fungsi komplek z2 – c, dengan memanfaatkan sifat-sifat fraktalnya yaitu antara lain sensitif terhadap nilai awal, kesamaan diri dan iteratif. Pertama, dibahas bagaimana menyembunyikan citra rahasia dalam suatu citra sampul yaitu citra himpunan Julia dari fungsi komplek z2 – c dengan nilai c dijadikan salah satu komponen dari kunci(key) dan juga nggunakan manipulasi warna (RGB) dari citra sampul, suatu pesan berupa citra rahasia yang sudah dikonversi dalam betuk matrik biner 0,1 dapat disembunyikan sehingga menghasilkan citra stego (stego image) yang secara visual sama dengan citra sampulnya dan diharapkan tahan terhadap serangan. Kemudian, dibuat program komputer yang mampu menyembunyikan dan mengambil kembali citra rahasia pada citra sampul himpunan. Dari analisis hasil program komputer yang dibuat, perbandingan antara citra sampul dan citra stego berukuran 512x512 pixel, didapat bahwa rata-rata RMSE 0,2305 dan rata-rata PSNR 60,88 db dari 12 set data uji, hal ini menunjukkan bahwa kedua citra sangat mirip sehingga sulit dibedakan mana citra yang memuat citra rahasia dengan ukuran citra rahasia paling besar 128x85 pixel atau 261.120 bits. Waktu proses penyembunyian citra rahasia rata-rata 1,626 detik (tidak termasuk waktu pembuatan citra sampul) sedangkan waktu proses pengambilan kembali citra rahasia rata-rata 4,526 detik

Optimal Image Based Information Hiding with One-dimensional Chaotic Systems and Dynamic Programming

Information hiding is a technology aimed at the secure hiding of important information into digital documents or media. In this paper, a new approach is proposed for the secure hiding of information into gray scale images. The hiding is performed in two stages. In the first stage, the binary bits in the sequence of information are shuffled and encoded with a set of integer keys and a system of one-dimensional logistic mappings. In the second stage, the resulting sequence is embedded into the gray values of selected pixels in the given image. A dynamic programming method is utilized to select the pixels that minimize the difference between a cover image and the corresponding stego image. Experiments show that this approach outperforms other information hiding methods by 13.1% in Peak Signal to Noise Ratio (PSNR) on average and reduces the difference between a stego image and its cover image to 0 in some cases.

Reference-free differential histogram-correlative detection of steganography: performance analysis

<span lang="EN-US">Recent <span>research has demonstrated the effectiveness of utilizing neural networks for detect tampering in images. However, because accessing a database is complex, which is needed in the classification process to detect tampering, reference-free steganalysis attracted attention. In recent work, an approach for least significant bit (LSB) steganalysis has been presented based on analyzing the derivatives of the histogram correlation. In this paper, we further examine this strategy for other steganographic methods. Detecting image tampering in the spatial domain, such as image steganography. It is found that the above approach could be applied successfully to other kinds of steganography with different orders of histogram-correlation derivatives. Also, the limits of the ratio stego-image to cover are considered, where very small ratios can escape this detection method unless </span> modified.</span>

Concealing a Secret Message in a Colour Image Using an Electronic Workbench

Steganography is the art of concealing security data in media, such as pictures, audio, video, text, and protocols. The objective of this paper is hiding a secret message in a colour image to prevent an attacker from accessing the message. This is important because more people use the Internet all the time and network connections are spread around the world. The hidden secret message uses two general algorithms that are embedded and extracted. This paper proposes a new algorithm to conceal a secret message in a colour image in LSB. This algorithm includes three phases: 1) dividing the colour image into a number of blocks, 2) concealing the secret message, and 3) transmitting the stego-image from the sender in a multiplexer network and receiving it through a demultiplexer network using an electronic workbench. The outcome of the new algorithm demonstrates good efficiency, high security, and robustness and is executed quickly. The system is evaluated through the measurements of mean square error, peak signal-to-noise ratio, correlation, histogram, and capacity.

Improved Deep Hiding/Extraction Algorithm to Enhance the Payload Capacity and Security Level of Hidden Information

Steganography algorithms have become a significant technique for preventing illegal users from obtaining secret data. In this paper, a deep hiding/extraction algorithm has been improved (IDHEA) to hide a secret message in colour images. The proposed algorithm has been applied to enhance the payload capacity and reduce the time complexity. Modified LSB (MLSB) is based on disseminating secret data randomly on a cover-image and has been proposed to replace a number of bits per byte (Nbpb), up to 4 bits, to increase payload capacity and make it difficult to access the hiding data. The number of levels of the IDHEA algorithm has been specified randomly; each level uses a colour image, and from one level to the next, the image size is expanded, where this algorithm starts with a small size of a cover-image and increases the size of the image gradually or suddenly at the next level, according to an enlargement ratio. Lossless image compression based on the run-length encoding algorithm and Gzip has been applied to enable the size of the data that is hiding at the next level, and data encryption using the Advanced Encryption Standard algorithm (AES) has been introduced at each level to enhance the security level. Thus, the effectiveness of the proposed IDHEA algorithm has been measured at the last level, and the performance of the proposed hiding algorithm has been checked by many statistical and visual measures in terms of the embedding capacity and imperceptibility. Comparisons between the proposed approach and previous work have been implemented; it appears that the intended approach is better than the previously modified LSB algorithms, and it works against visual and statistical attacks with excellent performance achieved by using the detection error (PE). Furthermore, the results confirmed that the stego-image with high imperceptibility has reached even a payload capacity that is large and replaces twelve bits per pixel (12-bpp). Moreover, testing is confirmed in that the proposed algorithm can embed secret data efficiently with better visual quality.

Disguise of Steganography Behaviour: Steganography Using Image Processing with Generative Adversarial Network

The deep learning based image steganalysis is becoming a serious threat to modification-based image steganography in recent years. Generation-based steganography directly produces stego images with secret data and can resist the advanced steganalysis algorithms. This paper proposes a novel generation-based steganography method by disguising the stego images into the kinds of images processed by normal operations (e.g., histogram equalization and sharpening). Firstly, an image processing model is trained using DCGAN and WGAN-GP, which is used to generate the images processed by normal operations. Then, the noise mapped by secret data is inputted into the trained model, and the obtained stego image is indistinguishable from the processed image. In this way, the steganographic process can be covered by the process of image processing, leaving little embedding trace in the process of steganography. As a result, the security of steganography is guaranteed. Experimental results show that the proposed scheme has better security performance than the existing steganographic methods when checked by state-of-the-art steganalytic tools, and the superiority and applicability of the proposed work are shown.

Asymmetric Data Hiding for Compressed Images with High Payload and Reversibility

Hiding secret data in digital images is an attractive topic in the information security research area. Because the data-embedded stego image looks exactly the same as a regular image, transmitting secret data with stego images does not draw the attention of eavesdroppers, thus fulfilling the goal of information security. Many reversible data hiding (RDH) methods for absolute moment block truncation coding (AMBTC) compressed images have been proposed. These methods hide secret data in an AMBTC-compressed image to produce a stego image and transmit it to the recipient. Upon receiving the stego image, the recipient can extract the secret data and recover the AMBTC-compressed image. In this paper, we propose an RDH scheme for AMBTC-compressed images with an asymmetric embedding rule. Using the AMBTC-compressed version as the basis, the proposed embedding scheme always modifies a pixel value toward its original value with a step size (bitrate) proportional to the gap width. Therefore, the visual quality of the stego image is better than the referred AMBTC version. Additionally, as a result of the adaptive bitrate strategy, the data embedding capacity of the proposed scheme outperforms that of state-of-the-art methods. The security of the resulting stego images was also tested by RS-steganalysis. Experimental results show that the overall performance of the proposed scheme is satisfactory. We revised it, please confirm.