GOOD PERFORMANCE IMAGES ENCRYPTION USING SELECTIVE BIT T-DES ON INVERTED LSB STEGANOGRAPHY

Transmitting image through the internet needs to be secured because of risk to be stolen. Security techniques that can be used for securing data especially image are cryptography and steganography. Combine these techniques can provide double protection in image security. In this research, we proposed the used of T-DES encryption with a selective bit to improve the time performance because time aspect is one of the important aspects of data transmission process. Four MSB of the secret image will be selected, then it will be encrypted using T-DES. After that, this encrypted results will be combined with other 4 LSB. This encryption scheme result will be embedded into a cover image using inverted LSB because inverted LSB can produce high imperceptible value. From 6 testing images which encrypted using proposed scheme present that proposed encryption scheme is twice faster than classic triple DES and slightly faster than double DES. While the embedding scheme can produce PSNR value above 40 dB with the range between 51 dB to 61 dB as well as SSIM which close to 1. This result denoted that proposed scheme generated good quality of stego images

A Combination of Inverted LSB, RSA, and Arnold Transformation to get Secure and Imperceptible Image Steganography

Securing images can be achieved using cryptography and steganography. Combining both techniques can improve the security of images. Usually, Arnold's transformation (ACM) is used to encrypt an image by randomizing the image pixels. However, applying only a transformation algorithm is not secure enough to protect the image. In this study, ACM was combined with RSA, another encryption technique, which has an exponential process that uses large numbers. This can confuse attackers when they try to decrypt the cipher images. Furthermore, this paper also proposes combing ACM with RSA and subsequently embedding the result in a cover image with inverted two-bit LSB steganography, which replaces two bits in the bit plane of the cover image with message bits. This modified steganography technique can provide twice the capacity of the previous method. The experimental result was evaluated using PSNR and entropy as the parameters to obtain the quality of the stego images and the cipher images. The proposed method produced a highest PSNR of 57.8493 dB and entropy equal to 7.9948

Randomly-based Stepwise Multi-Level Distributed Medical Image Steganography

Steganography deals with concealing sensitive information that can either be communicated across a network or stored in a secured location. The concealment of information is accomplished through the carrier, making data access by an unauthorized person more difficult. There are many stenographic techniques that have been used. Unfortunately, the hybrid-multi-level approach was ignored. For this reason, the current research utilized image steganography on a hybrid-multi level involving encryption, data compression, and two-stage high data concealment. The proposed technique can be used to conceal information in medical images without any distortion, allowing flexible and secure transfer capability. After using the Trible DES algorithm to encrypt the secret text at the beginning of the process, the next step involves embedding the secret encrypted cipher message into the host image while keeping the image intact. The findings indicate that the value of PSNR and NCC are satisfactory when compared to the sensitivity of the human eye. As a direct impact, the confidential message is hidden from the adversary. It can be seen that the PSNR value is quite high. Therefore, this indicates that the image after the stenographic process is relatively similar to the original image

Dual-image-based reversible data hiding scheme with integrity verification using exploiting modification direction

Abstract(#br)In this paper, a novel dual-image-based reversible data hiding scheme using exploiting modification direction (EMD) is proposed. This scheme embeds two 5-base secret digits into each pixel pair of the cover image simultaneously according to the EMD matrix to generate two stego-pixel pairs. By shifting these stego-pixel pairs to the appropriate locations in some cases, two meaningful shadows are produced. The secret data can be extracted accurately, and the cover image can be reconstructed completely in the data extraction and the image reconstruction procedure, respectively. Experimental results show that our scheme outperforms the comparative methods in terms of image quality and embedding ratio. Pixel-value differencing (PVD) histogram analysis reveals that our scheme..

Optimization of medical image steganography using n-decomposition genetic algorithm

Protecting patients' confidential information is a critical concern in medical image steganography. The Least Significant Bits (LSB) technique has been widely used for secure communication. However, it is susceptible to imperceptibility and security risks due to the direct manipulation of pixels, and ASCII patterns present limitations. Consequently, sensitive medical information is subject to loss or alteration. Despite attempts to optimize LSB, these issues persist due to (1) the formulation of the optimization suffering from non-valid implicit constraints, causing inflexibility in reaching optimal embedding, (2) lacking convergence in the searching process, where the message length significantly affects the size of the solution space, and (3) issues of application customizability where different data require more flexibility in controlling the embedding process. To overcome these limitations, this study proposes a technique known as an n-decomposition genetic algorithm. This algorithm uses a variable-length search to identify the best location to embed the secret message by incorporating constraints to avoid local minimum traps. The methodology consists of five main phases: (1) initial investigation, (2) formulating an embedding scheme, (3) constructing a decomposition scheme, (4) integrating the schemes' design into the proposed technique, and (5) evaluating the proposed technique's performance based on parameters using medical datasets from kaggle.com. The proposed technique showed resistance to statistical analysis evaluated using Reversible Statistical (RS) analysis and histogram. It also demonstrated its superiority in imperceptibility and security measured by MSE and PSNR to Chest and Retina datasets (0.0557, 0.0550) and (60.6696, 60.7287), respectively. Still, compared to the results obtained by the proposed technique, the benchmark outperforms the Brain dataset due to the homogeneous nature of the images and the extensive black background. This research has contributed to genetic-based decomposition in medical image steganography and provides a technique that offers improved security without compromising efficiency and convergence. However, further validation is required to determine its effectiveness in real-world applications