Steganography is a technology which is utilized in securing information through hiding data over another data which can be stored or passed over public network without a clue that secret data is hidden in the cover medium. This article focus on securing and hiding the data through transform domain techniques used in Image, Audio and Video steganography. The review study throws light on the algorithm and properties of transform domain techniques and its benefits to utilize in securing data. Parameters such as imperceptibility, capacity and robustness are evaluated for discrete cosine transform (DCT) and discrete wavelet transform (DWT). Key-words—Steganography; Discrete cosine transform; Discrete Fourier Transform; Discrete Wavelet Transform; Network security; Secure Communication Received: August 26, 2020 . Revised: November 16, 2020. Accepted: January 15, 2021. Published: January 22, 2021.

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Securing Data: A Study on Different Transform Domain Techniques

In the latest years, there is an increasing emphasis on DICOM medical images, especially in digital medical images transmission to e-health services. Besides, the confidentiality and protection of patients’ secure information need more attention and research. In this paper, we propose an enhanced medical image steganographic algorithm to hide patients’ secure information in their medical images. The proposed algorithm has a higher level of confidentiality while maintaining a higher quality of the medical image and a higher embedding capacity and robustness. The proposed algorithm has two main steps. The medical cover image is decomposed using an integer wavelet filter in the first step. Moreover, the patients’ confidential information is processed using the Arithmetic Coding (AC) and Data Encryption Standard (DES) algorithms to be compressed and encrypted before of the embedding process. In the second step, the insignificant coefficients are selected from the integer wavelet high-frequency subbands of the transformed medical image, and finally, both the target cover bits and the secret bits are grouped during the injection process. The performance of our algorithm was evaluated using different evaluation metrics. The obtained results show that our algorithm outperforms existing ones, with a higher embedding capacity, and a lower imperceptibility. The proposed algorithm can be applied in hospitals and health care canters worldwide. 

Hiding patients’ medical reports using an enhanced wavelet steganography algorithm in DICOM images

Image Steganography using Dynamic Threshold based on Discrete Cosine Transform

This paper introduces an approach which can be discriminated between normal images and images containing hidden information. After applying one scale 2D Haar Wavelet Transform (2DHWT) on the image, a new image sub-band is configured contains the Lower Coefficients Value (LCV) among image detail sub-bands. The differences in three directions between adjacent pixels of approximation and LCV image sub-bands are modeled utilizing 2nd order Markov chains. Components of sample transition probability matrices (TPMs) are then utilized as feature vector for a proposed approach implemented by linear support vector machine (SVM) and Naive Bayes (NB) classifiers. Proposed approach is evaluated by detection accuracy of three common image embedding methods at three quality factors (QFs) with five different embedding rates. The comparison in using approximation sub-band with the other detail sub-bands reveals that the presented feature vector offers an improvement in detection accuracy.

Identify the Presence of Hidden Information Based on Lower Coefficients Value of 2DHWT Sub-bands

Information is a vitalthing that needs to be secured and well protected during transmission between two or more parties over the internet. This can be achieved by steganography technology. Steganography is the concealing science in which the information is concealed inside other information in a way that the concealed information cannot be detectable by the human eye. Many ways are available to hide data inside a cover media for example text, image, and audio steganography, but image steganography is the most utilized technique among the others. Secure image steganography has a high-security level than traditional technique by combining steganography with cryptography due to encrypting secret information by cryptography algorithm before embedding it into the cover media by steganography algorithm. In this paper,a systematic review has been presented about secure image steganography and its renowned types. Many researchers proposed secure image steganography by using various cryptography and steganography algorithms which have been reviewed. The least significant bit ‘LSB’ was the renowned steganography algorithm which has been used by researchers due to its simplicity, while various cryptography algorithms like advanced encryption standard (AES) and blowfishhave been used to propose secure image steganography in the reviewed papers. The comparison among the reviewed papers indicated that the LSB with hash-RSA gave a greater peak signal-noise ratio ‘PSNR’ value than the others which was 74.0189 dB.

http://ijaas.iaescore.com/index.php/IJAAS/article/download/20378/12938

A systematic overview of secure image steganography

Recently the Discrete-Wavelet-Transform (DWT) has been represented as signal processing powerful tool to separate the signal into its band frequency components. In this paper, improvement of the steganography techniques by hiding the required message into the suitable frequency band is presented. The results show that the increase of the message length will reduce the Peak Signal to Noise Ratio (PSNR), while the PSNR increases with the increasing the DWT levels. It should be noted that the PSNR reduction was from -13.8278 to -17.77208 when increasing the message length from 161 to 505 characters. In this context, the PSNR is increased from -13.8278 to 7.0554 and from -17.7208 to 1.7901 when the DWT increased from level (1) to level (2).

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Rula S. Khudhair

Papers

Improvement of Image Steganography Using Discrete Wavelet Transform