This paper presents a literature review of image steganography techniques in the spatial domain for last 5 years. The research community has already done lots of noteworthy research in image steganography. Even though it is interesting to highlight that the existing embedding techniques may not be perfect, the objective of this paper is to provide a comprehensive survey and to highlight the pros and cons of existing up-to-date techniques for researchers that are involved in the designing of image steganographic system. In this article, the general structure of the steganographic system and classifications of image steganographic techniques with its properties in spatial domain are exploited. Furthermore, different performance matrices and steganalysis detection attacks are also discussed. The paper concludes with recommendations and good practices drawn from the reviewed techniques.

Image steganography in spatial domain: A survey

The rapid spread in digital data usage in many real life applications have urged new and effective ways to ensure their security. Efficient secrecy can be achieved, at least in part, by implementing steganograhy techniques. Novel and versatile audio steganographic methods have been proposed. The goal of steganographic systems is to obtain secure and robust way to conceal high rate of secret data. We focus in this paper on digital audio steganography, which has emerged as a prominent source of data hiding across novel telecommunication technologies such as covered voice-over-IP, audio conferencing, etc. The multitude of steganographic criteria has led to a great diversity in these system design techniques. In this paper, we review current digital audio steganographic techniques and we evaluate their performance based on robustness, security and hiding capacity indicators. Another contribution of this paper is the provision of a robustness-based classification of steganographic models depending on their occurrence in the embedding process. A survey of major trends of audio steganography applications is also discussed in this paper.

https://link.springer.com/content/pdf/10.1186%2F1687-4722-2012-25.pdf

Comparative study of digital audio steganography techniques

Steganography has been proposed as a new alternative technique to enforce data security. Lately, novel and versatile audio steganographic methods have been proposed. A perfect audio Steganographic technique aim at embedding data in an imperceptible, robust and secure way and then extracting it by authorized people. Hence, up to date the main challenge in digital audio steganography is to obtain robust high capacity steganographic systems. Leaning towards designing a system that ensures high capacity or robustness and security of embedded data has led to great diversity in the existing steganographic techniques. In this paper, we present a current state of art literature in digital audio steganographic techniques. We explore their potentials and limitations to ensure secure communication. A comparison and an evaluation for the reviewed techniques is also presented in this paper.

A view on latest audio steganography techniques

Steganography is an art of obscuring data inside another quotidian file of similar or varying types. Hiding data has always been of significant importance to digital forensics. Previously, steganography has been combined with cryptography and neural networks separately. Whereas, this research combines steganography, cryptography with the neural networks all together to hide an image inside another container image of the larger or same size. Although the cryptographic technique used is quite simple, but is effective when convoluted with deep neural nets. Other steganography techniques involve hiding data efficiently, but in a uniform pattern which makes it less secure. This method targets both the challenges and make data hiding secure and non-uniform.

/pdf/hiding-data-in-images-using-cryptography-and-deep-neural-1ba39fnav2.pdf

Hiding Data in Images Using Cryptography and Deep Neural Network

Information hiding researchers have been exploring techniques to improve the security of transmitting sensitive data through an unsecured channel. This paper proposes an audio steganography model for secure audio transmission during communication based on fractal coding and a chaotic least significant bit or also known as HASFC. This model contributes to enhancing the hiding capacity and preserving the statistical transparency and security. The HASFC model manages to embed secret audio into a cover audio with the same size. In order to achieve this result, fractal coding is adopted which produces high compression ratio with the acceptable reconstructed signal. The chaotic map is used to randomly select the cover samples for embedding and its initial parameters are utilized as a secret key to enhancing the security of the proposed model. Unlike the existing audio steganography schemes, The HASFC model outperforms related studies by improving the hiding capacity up to 30% and maintaining the transparency of stego audio with average values of SNR at 70.4, PRD at 0.0002 and SDG at 4.7. Moreover, the model also shows resistance against brute-force attack and statistical analysis.

High capacity, transparent and secure audio steganography model based on fractal coding and chaotic map in temporal domain

In this paper, we present a unified algorithm for phase and magnitude speech spectra data hiding. The phase and the magnitude speech spectra are concurrently investigated to increase the capacity and the security of the embedded information. The proposed algorithm in this paper is based on finding secure spectral embedding areas in wideband magnitude speech spectrum. Our approach exploits these areas to hide data in both speech components (i.e., phase and magnitude). The embedding locations and hiding capacity are defined according to a controlled acceptable distortion in the magnitude spectrum. The latter is expressed as a set of parameters controlled by the sender. Consequently, the hiding capacity and the locations of concealed data change for each data communication instance to further prevent malicious intrusions. Objective results show that the presented algorithm in this paper secures hidden data and achieves interesting tradeoffs between the hiding capacity and the speech quality. Copyright © 2013 John Wiley & Sons, Ltd.

https://onlinelibrary.wiley.com/doi/pdf/10.1002/sec.644

Unified phase and magnitude speech spectra data hiding algorithm

In this paper we present a new method for text-in-speech Fast Fourier Transform (FFT) based steganography. Our method exploits high energetic magnitude frequency components of speech spectrum to hide the secret text. The energy level of each magnitude component is evaluated, and considered only if it is high enough to embed secret data. A frequency masking threshold is then calculated for each energetic frequency magnitude component to decide where to embed the secret text. As a result, the initial energy of the cover speech spectrum is slightly modified and the distortion error is always kept under the mask. The objective and subjective evaluations show that introducing the energy-based frequency masking opens new frontiers in text-in-speech steganography since higher bit rate text embedding was achieved while obtaining a stego-speech with unnoticeable distortion.

Dynamic energy based text-in-speech spectrum hiding using speech masking properties

Methods applied to ensure privacy of digital data became essential in many real life applications. Efficient secrecy can be achieved, at least in part, by implementing steganography techniques. In this paper, we present a technique that limits the impact of high data capacity embedding on the quality of stego wideband speech. Our method uses the energy of each frequency bin component to determine the maximum number of bits that can be confined without inducing any noticeable distortion on the cover speech. To guarantee good quality of stego speech, the embedding in the selected frequency components occurs below a well defined distortion level to limit the impact of the hiding on the stego-speech. The algorithm uses multiple parameters that can be adjusted by the sender to render the steganalysis work more challenging. The objective and subjective results show that this approach is robust to noise addition and maintains a very good quality of the cover signal while achieving high hiding capacity.

Fatiha Djebbar

Papers

Comparative study of digital audio steganography techniques

A view on latest audio steganography techniques

Unified phase and magnitude speech spectra data hiding algorithm

Dynamic energy based text-in-speech spectrum hiding using speech masking properties

Controlled Distortion for High Capacity Data-in-Speech Spectrum Steganography