In the Internet of Things, it is more important than ever to effectively address the problem of secure transmission based on steganographic substitution by synthesizing digital sensor data. In this case, the degree to which the grayscale message is obscured is a necessary issue. To ensure information security in IoT systems, various methods are used and information security problems are solved to one degree or another. The article proposes a method and algorithm for a computer image in grayscale, in which the value of each pixel is one sample, representing the amount of light, carrying only information about the intensity. The proposed method in grayscale using steganographic coding provides a secure implementation of data transmission in the IoT system. Study results were analyzed using PSNR (Peak Signal to Noise Ratio).

Algorithmic method of security of the Internet of Things based on steganographic coding

https://link.springer.com/content/pdf/10.1186/s42787-019-0061-6.pdf

An efficient steganographic technique for hiding data

Digital image steganography survey and investigation (goal, assessment, method, development, and dataset)

Since the number of internet users is increasing and sensitive information is exchanging continuously, data security has become a problem. Image steganography is one of the ways to exchange secret data securely using images. However, several issues need to be mitigated, especially in the imperceptibility (security) aspect, which is the process of embedding secret data in the images that can be vulnerable to attacks. This paper focuses on developing a secure method for hiding secret messages in an image, based on the standard Least Significant Bit (LSB). Before proceeding with the embedding stage, the secret message's size is reduced by compression using the Huffman algorithm, followed by two operations, which are the Boolean operation Exclusive-NOR (XNOR) operation and the Fibonacci algorithm when selecting pixels to embed the secret message. As a result of these processes, a stego-image is created with two secret keys. We obtained promising results against standard images with higher Peak Signal-to-Noise Ratio (PSNR) values of 66.6170, 65.8928, and 65.9386 dB for Lena.bmp, Baboon.bmp, and Pepper.bmp, respectively, as compared to other state-of-the-art schemes. The evaluation stage proves the increasing level of security as well as imperceptibility.

/pdf/high-security-image-steganography-technique-using-xnor-3er2uw3dts.pdf

High-Security Image Steganography Technique using XNOR Operation and Fibonacci Algorithm

The ever-escalating attacks on the internet network are due to rapid technological growth. In order to surmount such challenges, multi-layer security algorithms were developed by hybridizing cryptography and steganography techniques. Consequently, the overall memory size became enormous while hybridizing these techniques. On the other side, the least significant bit (LSB) and modified LSB replacing approaches could provide the variability as detected by steganalysis technique, most found to be susceptible to attack too due to numerous reasons. To overcome these issues, in this paper a lightweight and optimized data hiding algorithm is proposed which consume less memory, provide less variability, and robust against histogram attacks. The proposed steganography system was achieved in two stages. First, data was encrypted using lightweight BORON cipher that only consumed less memory as compared to conventional algorithm such as 3DES, AES. Second, the encrypted data was hidden in the complemented or non-complemented form to obtain minimal variability. The performance of the proposed technique was evaluated in terms of avalanche effect, visual quality, embedding capacity and peak signal to noise ratio (PSNR). The results revealed that the lightweight BORON cipher could produce approximate same avalanche effect as the AES algorithm produced. Furthermore, the value of PSNR had shown much improvement in comparison to optimization algorithm GA.

/pdf/lightweight-and-optimized-multi-layer-data-hiding-using-2dugo4821p.pdf

Lightweight and Optimized Multi-Layer Data Hiding using Video Steganography Paper

Steganography is an art of disguising the fact that communication is going on by concealing information in other information. In general, the communication carrier can be files in many formats; however, digital images are the most common due to their frequent use on the Internet. This paper introduces an improvement on the standard least significant bit (LSB)-based image steganography technique and proposes the bit inversion method that improves the stego-images quality in 24-bit colour image. A stegoimage is the outcome of an image (usually called the cover image), after a secret message is hidden in it. In this technique, the LSB’s of some pixels of the cover image are inverted, when inputs of specific patterns of some bits related to the pixels are found. In this way, less number of pixels is modified in comparison to the standard LSB method. Our focus is to obtain a high value ratio of the Peak Signal-to-Noise (PSNR) of the stego-image, to make sure that both stego-image and the original image are difficult to discern by human eyes. The proposed bit inversion method starts with the last LSBs of both green and blue colour planes that will be replaced by the first and the second most significant bits (MSB) of the secret image. The proposed method introduces two additional levels of security to the standard LSB steganography. The first level is that because only the green and blue colours are used, instead of three colors red, green, and blue in the standard LSB, the red colour will act as noise data, and thus increases the complexity of an attacker, when he/she tries to retrieve the secret message. The second level exploits the new bit inversion technique that reverses the bits of the image pixels after applying the standard LSB. Experiments have been conducted using a collection of standard images to evaluate the proposed technique, which give the Peak Signal-toNoise Ratio (PSNR) values of 72, 61, and 70 for Lena.jpg, Babbon.jpg, and Pepper.jpg respectively. From the experiment, we also observed that by using the bit inverse technique, less numbers of pixels are modified compared with the standard LSB method.

An improved LSB image steganography technique using bit-inverse in 24 bit colour image

There has been a persistent requirement for safeguarding documents and the data they contain, either in printed or electronic form. This is because the fabrication and faking of documents is prevalent globally, resulting in significant losses for individuals, societies, and industrial sectors, in addition to national security. Therefore, individuals are concerned about protecting their work and avoiding these unlawful actions. Different techniques, such as steganography, cryptography, and coding, have been deployed to protect valuable information. Steganography is an appropriate method, in which the user is able to conceal a message inside another message (cover media). Most of the research on steganography utilizes cover media, such as videos, images, and sounds. Notably, text steganography is usually not given priority because of the difficulties in identifying redundant bits in a text file. To embed information within a document, its attributes must be changed. These attributes may be non-displayed characters, spaces, resized fonts, or purposeful misspellings scattered throughout the text. However, this would be detectable by an attacker or other third party because of the minor change in the document. To address this issue, it is necessary to change the document in such a manner that the change would not be visible to the eye, but could still be decoded using a computer. In this paper, an overview of existing research in this area is provided. First, we provide basic information about text steganography and its general procedure. Next, three classes of text steganography are explained: statistical and random generation, format-based methodologies, and linguistics. The techniques related to each class are analyzed, and particularly the manner in which a unique strategy is provided for hiding secret data. Furthermore, we review the existing works in the development of approaches and algorithms related to text steganography; this review is not exhaustive, and covers research published from 2016 to 2021. This paper aims to assist fellow researchers by compiling the current methods, challenges, and future directions in this field.

Mohammed Abdul Majeed

Papers

An improved LSB image steganography technique using bit-inverse in 24 bit colour image

A Review on Text Steganography Techniques