A combination of least significant bit and deflate compression for image steganography

Steganography is one of the cryptography techniques where secret information can be hidden through multimedia files such as images and videos. Steganography can offer a way of exchanging secret and encrypted information in an untypical mechanism where communicating parties can only interpret the secret message. The literature has shown a great interest in the least significant bit (LSB) technique which aims at embedding the secret message bits into the most insignificant bits of the image pixels. Although LSB showed a stable performance of image steganography yet, many works should be done on the message part. This paper aims to propose a combination of LSB and Deflate compression algorithm for image steganography. The proposed Deflate algorithm utilized both LZ77 and Huffman coding. After compressing the message text, LSB has been applied to embed the text within the cover image. Using benchmark images, the proposed method demonstrated an outperformance over the state of the art. This can proof the efficacy of using Deflate as a data compression prior to the LSB embedding.

A New Method to Estimate Peak Signal to Noise Ratio for Least Significant Bit Modification Audio Steganography

Audio steganography is implemented based on three main features: capacity, robustness, and imperceptibility, but simultaneously implementing them is still a challenge. Embedding data at the Least Significant Bit (LSB) of the audio sample is one of the most implemented audio steganography methods because the method will give high capacity and imperceptibility. However, LSB has the lowest robustness among all common methods in audio steganography. To cater to this problem, researchers increased the depth of the embedding level from fourth to sixth and eighth LSB level to improve its robustness feature. However, consequently, the imperceptibility feature, which is commonly measured by Peak Signal to Noise Ratio (PSNR), is reduced due to the trade-off between imperceptibility and robustness. Currently, the lack of study on the estimation of the PSNR for audio steganography has caused the early assessment of the imperceptibility-robustness trade-off difficult. Therefore, a method to estimate PSNR, known as PSNR Estimator (PE), is introduced to enable early evaluation of imperceptibility feature for each stego-file produced by the audio steganography, which is important for the utilisation of embedding. The proposed PE estimates the PSNR based on the pattern collected from the embedment at different levels. From the evaluation, the proposed method has 99.9% of accuracy in estimating PSNR values at different levels. In comparison with the Mazdak Method, the proposed method performs better in all situations. In conclusion, the proposed PE can be used as a reference for embedding and further reducing the calculation complexity in finding the feasible value to minimise the trade-off between robustness and imperceptibility.

Design secure multi-level communication system based on duffing chaotic map and steganography

Cryptography and steganography are among the most important sciences that have been properly used to keep confidential data from potential spies and hackers. They can be used separately or together. Encryption involves the basic principle of instantaneous conversion of valuable information into a specific form that unauthorized persons will not understand to decrypt it. While steganography is the science of embedding confidential data inside a cover, in a way that cannot be recognized or seen by the human eye. This paper presents a high-resolution chaotic approach applied to images that hide information. A more secure and reliable system is designed to properly include confidential data transmitted through transmission channels. This is done by working the use of encryption and steganography together. This work proposed a new method that achieves a very high level of hidden information based on non-uniform systems by generating a random index vector (RIV) for hidden data within least significant bit (LSB) image pixels. This method prevents the reduction of image quality. The simulation results also show that the peak signal to noise ratio (PSNR) is up to 74.87 dB and the mean square error (MSE) values is up to 0.0828, which sufficiently indicates the effectiveness of the proposed algorithm.

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>

Crypto-Steganographic Method to Protect Secret Messages

Multiple methods are used to hide secret messages in digital color images, and the most important and most common is the least significant bit (LSB) method. The LSB method is a known and exposed method, and anyone with programming experience can retrieve the secret message embedded in the digital image. In this paper research we will add some enhancements to improve the security level of LSB method to protect the embedded secret message from being hacked. A simple method of secret message cryptography will be used to encrypt the secret message before bedding it using LSB method. The method will be based on using color image as an image_key; this image_key will be resized to generate the needed secret private key used to encrypt-decrypt secret message. The length and the contents of the generated private key will dynamically change depending on the message length and the selected image_key. The selected image_key will be kept in secret without transmission and will be known only by the sender and receiver and it can be changed any time when needed. The proposed crypto_steganographic method will be implemented to show how it will increase the level o secret message protection.

Influence of Analog-To-Digital Conversion and Decimation Parameters on the Signal-To-Noise Ratio in the Radar Path

Introduction. The digital representation of received radar signals has provided a wide range of opportunities for their processing. However, the used hardware and software impose some limits on the number of bits and sampling rate of the signal at all conversion and processing stages. These limitations lead to a decrease in the signal-to-interference ratio due to quantization noise introduced by powerful components comprising the received signal (interfering reflections; active noise interference), as well as the attenuation of a low-power reflected signal represented by a limited number of bits. In practice, the amplitude of interfering reflections can exceed that of the signal reflected from the target by a factor of thousands.Aim. In this connection, it is essential to take into account the effect of quantization noise on the signal-tointerference ratio.Materials and methods. The article presents expressions for calculating the power and power spectral density (PSD) of quantization noise, which take into account the value of the least significant bit of an analog-to-digital converter (ADC) and the signal sampling rate. These expressions are verified by simulating 4-, 8- and 16-bit ADCs in the Mathcad environment.Results. Expressions are derived for calculating the quantization noise PSD of interfering reflections, which allows the PSD to be taken into account in the signal-to-interference ratio at the output of the processing chain. In addition, a comparison of decimation options (by discarding and averaging samples) is performed drawing on the estimates of the noise PSD and the signal-to-noise ratio.Conclusion. Recommendations regarding the ADC bit depth and sampling rate for the radar receiver are presented.

Analisis Digital Watermarking untuk Otentikasi pada Citra Manipulasi Menggunakan Metode Least Significant Bit

The use of digital platforms has both positive and negative effects. Many criminals who manipulate images for personal gain, so as to harm the copyright holder (ownership) of the image. The purpose of the study was to detect false imagery generated by copy-move, splicing, and retouching techniques. The method used is the Least Significant Bit (LSB) method as a watermarking technique and its detection features. The insertion process is carried out on watermark images into the cover image as the container media. Image owners can authenticate to prove the originality of the image when the extraction process is done, the image manipulation is successfully detected because it is damaged. The test results showed that the digital watermarking technique with the Least Significant-Bit method is able to protect and prove the authenticity of the image. It was concluded that the results of comparison of watermark extraction on the original image and manipulation image saw a very significant difference in terms of visual and calculation with MSE, RMSE, and PSNR parameters.

LSB-based Audio Steganographical Framework for Securing Data in Transit

The benefits that individuals and organizations derive from the digital era comes with its own challenges. Globally, data has become one of the greatest assets for decision making and operational improvements among businesses, government agencies and even individuals. Data on its own and at its source does not make so much contribution to business processes. Data is transmitted from one location to another towards attainment of its goal as a critical resource in decision making. However, data including sensitive or confidential ones are transmitted via public channels such as the Internet. The data so transmitted via the Internet is vulnerable to interception and unauthorized manipulation. This demands that data in transit is protected from the prying eyes of the malicious internet users. One of such strategies for transmitting data via public channels such as the Internet without attracting attention from intruders is steganography. In this paper, the least significant bit algorithm was used with an audio file for hiding data in transit. The algorithm used in this research proves to be one of the simplest ways of securing data using audio steganography. The method employed the LSB technique by using audio files as the stego object for the final implementation in the Java programming language. The experimental results proved to be one of the best methods of implementing steganography. The accuracy of the stego objects shows high quality, and similarity scores with an improved processing time.

LSBR Speech Steganalysis Based on Percent of Equal Adjacent Samples

Wide utilization of audio files has attracted the attention of cyber-criminals to employ this media as a cover for their concealed communications. As a countermeasure and to protect cyberspace, several techniques have been introduced for steganalysis of various audio formats, such as MP3, VoIP, etc. The combination of machine learning and signal processing techniques has helped steganalyzers to obtain higher accuracies. However, as the statistical characteristics of a normal audio file differ from the speech ones, the current methods cannot discriminate clean and stego speech instances efficiently. Another problem is the high numbers of extracted features and analysis dimensions that drastically increase the implementation cost. To tackle these, this paper proposes the Percent of Equal Adjacent Samples (PEAS) feature for single-dimension least-significant-bit replacement (LSBR) speech steganalysis. The model first classifies the samples into speech and silence groups according to a threshold which has been determined through extensive experiments. It then uses an MLP classifier to detect stego instances and determine the embedding ratio. PEAS steganalysis detects 99.8% of stego instances in the lowest analyzed embedding ratio — 12.5% — and its sensitivity increases to 100% for the ratios of 37.5% and above.

Image Watermarking Approach Using LSB and Laplacian Filter

With the growth of information technologies, E-industry safety has recently become the mutual attention of education and business firms. Digital image watermarking is a technique that refers to the security of multimedia data. It is a process referred to the security and authentication of a digital image, video, and audio by embedding a watermark. Watermarking technique applies a number of variable editions to the host content, where the addition is related to embed information. In the past, researchers develop multiple simple watermarking techniques, today race is to find a region where the watermark is imperceptible and have a high payload. In this paper, an invisible image watermarking technique based on the least significant bit (LSB) and laplacian filter is proposed. The original image is divided into blocks and the laplacian filter is applied on each block. Laplacian is a derivative filter that uses the second derivate to find out the area of rapid changes in the image and the least significant bit is a technique to embed a watermark into the bit positions. Watermark is embedded on these regions which is favourable in achieving high desirable properties. This technique shows strong robustness against image processing and geometrical attacks. In evaluation with state of art methods, the proposed technique shows satisfactory progress.