An Adaptive FLV Steganography Approach Using Simulated Annealing

Data-hiding using steganography algorithm becomes an important technique to prevent unauthorized users to have access to a secret data. In this paper, steganography algorithm has been constructed to hide a secret data in a gray and a color images, this algorithm is named deep hiding/extraction algorithm (DHEA) to modify multi-level steganography (MLS). The suggested hiding algorithm is based on modified least significant bit (MDLSB) to scatter data in a cover-image and it utilizes a number of levels; where each level perform hiding data on a gray image except the last level that applies a color image to keep secret data. Furthermore, proper randomization approach with two layers is implemented; the first layer uses random pixels selection for hiding a secret data at each level, while the second layer implements at the last level to move randomly from segment to the others. In addition, the proposed hiding algorithm implements an effective lossless image compression using DEFLATE algorithm to make it possible to hide data into a next level. Dynamic encryption algorithm based on Advanced Encryption Standard (AES) is applied at each level by changing cipher keys (Ck) from level to the next, this approach has been applied to increase the security and working against attackers. Soft computing using a meta-heuristic approach based on artificial bee colony (ABC) algorithm has been introduced to achieve smoothing on pixels of stego-image, this approach is effective to reduce the noise caused by a hidden large amount of data and to increase a stego-image quality on the last level. The experimental result demonstrates the effectiveness of the proposed algorithm with bee colony DHA-ABC to show high-performing to hide a large amount of data up to four bits per pixel (bpp) with high security in terms of hard extraction of a secret message and noise reduction of the stego-image. Moreover, using deep hiding with unlimited levels is promising to confuse attackers and to compress a deep sequence of images into one image.

Section: Related Workmentioning

confidence: 99%

Modified Multi-Level Steganography to Enhance Data Security

Elshare¹,

El-Emam²

2022

“…Bawaneh developed a random LSB image steganography system (LCG) by using a linear congruent generator (LCG) [3]. The system within the RGB color picture inserted the hidden message in random positions which LCG developed.…”

Section: Related Workmentioning

confidence: 99%

“…Today in the digital world, various types of files may be used as cover of secret data, like, audio, text, image, or video. The steganography methods could be classified as injection, substitution, and distortion or generation due to variations in the procedures carried out to do the embedding process [3].…”

Section: Introductionmentioning

confidence: 99%

“…PSNR is deemed as a reflection to value of MSE; it grants an indication about the noise or the modification that is in the Stego image. After studying most of the proposed systems that work on hiding data that were published previously [1], [2], [3], [15], it became clear that some of them work on hiding data in the least significant bits, either in a sequential or random way, while others work on dividing the image and then hiding secret message data in different parts depending on a previously defined function or using some artificial intelligence methods. The current system, which is being studied, hides three bytes in a location in the image, which is built using Mandelbrot equations, which makes it difficult to compare it with the methods that were previously published.…”

mentioning

confidence: 99%

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An Adaptive Fractal Image Steganography Using Mandelbrot and Linear Congruent Generator

J. Bawaneh,

Obeidat,

Al-Hazaimeh

et al. 2023

Despite the advancements that occurred in the field of technology, information security (i.e., IS) is still deemed important and critical topic. It is still especially deemed so during the transfer process. In this research, a new approach is proposed for hiding information through the use of iterated function systems (i.e., IFS) from Fractals. This approach employs the main feature of fractals that concentrate on the idea that hackers who seek to find the hidden data shall not be able of locating it. Therefore, there is a need to carry out a decoding process in the aim of revering the conversion for securing the transmitted information. In this research, the secure information is hidden inside a fractal Mandelbrot image using the Linear Congruent Generator (i.e., LCG). Regarding the proposed system, it generates the fractal image through the use of the predefined knowledge gained from the hider site that works as a host for different types of secret messages. The knowledge that comes from the key of image dimensions, parameters of Mandelbrot, LCG key, and key agreement of cryptography method, which makes Stego-image analyses of hidden data unacceptable without the correct knowledge. Based on the results that are obtained through carrying out experiments showed the proposed method meets all the requirements for steganography. Such requirements include: the ones related to capacity, visual appearance, undetectability, robustness against extraction (i.e., security), and hit the highest capacities with a visual appearance of high quality.

“…The clustering technique of the color image is used to protect the embedded steganography from attacks. Bawaneh et al in [18] proposed a secure technique called flash video file steganography that saves the quality of video frames. Their proposed technique is able to hide different types of secret message inside the cover image.…”

Section: Proposed Algorithmmentioning

confidence: 99%

Multi-Stage Protection Using Pixel Selection Technique for Enhancing Steganography

Abuzanouneh¹,

Hadwan

2022

Steganography and data security are extremely important for all organizations. This research introduces a novel stenographic method called multi-stage protection using the pixel selection technique (MPPST). MPPST is developed based on the features of the pixel and analysis technique to extract the pixel's characteristics and distribution of cover-image. A pixel selection technique is proposed for hiding secret messages using the feature selection method. The secret file is distributed and embedded randomly into the stego-image to make the process of the steganalysis complicated. The attackers not only need to deter which pixel values have been selected to carry the secret file, they also must rearrange the correct sequence of pixels. MPPST generates a complex key that indicates where the encrypted elements of the binary sequence of a secret file are. The analysis stage undergoes four stages, which are the calculation of the peak signal-to-noise ratio, mean squared error, histogram analysis, and relative entropy. These four stages are used to demonstrate the characteristics of the cover image. To evaluate the proposed method, MPPST is compared to the standard technique of Least Significant Bit (LSB) and other algorithms from the literature. The experimental results show that MPPST outperforms other algorithms for all instances and achieves a significant security enhancement.