A Novel Technique for Data Steganography

Hindi, Amjad; Dwairi, Majed O.; Alqadi, Ziad

doi:10.48084/etasr.2955

Cited by 18 publications

(12 citation statements)

References 11 publications

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“…This section highlights different steganography techniques presented in the literature [14][15][16][17][18][19][20][21][22][23][24][25][26][27][28]. Tab.…”

Section: Literature Reviewmentioning

confidence: 99%

Novel Ransomware Hiding Model Using HEVC Steganography Approach

Almomani¹,

Alkhayer²,

El‐Shafai³

2022

Computers, Materials &Amp; Continua

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Ransomware is considered one of the most threatening cyberattacks. Existing solutions have focused mainly on discriminating ransomware by analyzing the apps themselves, but they have overlooked possible ways of hiding ransomware apps and making them difficult to be detected and then analyzed. Therefore, this paper proposes a novel ransomware hiding model by utilizing a block-based High-Efficiency Video Coding (HEVC) steganography approach. The main idea of the proposed steganography approach is the division of the secret ransomware data and cover HEVC frames into different blocks. After that, the Least Significant Bit (LSB) based Hamming Distance (HD) calculation is performed amongst the secret data's divided blocks and cover frames. Finally, the secret data bits are hidden into the marked bits of the cover HEVC frame-blocks based on the calculated HD value. The main advantage of the suggested steganography approach is the minor impact on the cover HEVC frames after embedding the ransomware while preserving the histogram attributes of the cover video frame with a high imperceptibility. This is due to the utilization of an adaptive steganography cost function during the embedding process. The proposed ransomware hiding approach was heavily examined using subjective and objective tests and applying different HEVC streams with diverse resolutions and different secret ransomware apps of various sizes. The obtained results prove the efficiency of the proposed steganography approach by achieving high capacity and successful embedding process while ensuring the hidden ransomware's undetectability within the video frames. For example, in terms of embedding quality, the proposed model achieved a high peak signal-to-noise ratio that reached 59.3 dB and a low mean-square-error of 0.07 for the examined HEVC streams. Also, out of 65 antivirus engines, no engine could detect the existence of the embedded ransomware app.

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“…This section highlights different steganography techniques presented in the literature [14][15][16][17][18][19][20][21][22][23][24][25][26][27][28]. Tab.…”

Section: Literature Reviewmentioning

confidence: 99%

Novel Ransomware Hiding Model Using HEVC Steganography Approach

Almomani¹,

Alkhayer²,

El‐Shafai³

2022

Computers, Materials &Amp; Continua

View full text Add to dashboard Cite

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“…Other used methods are based on wavelet packet tree (WPT) decomposition [20], [21], [22], these methods are efficient, but it is difficult to select the number of decomposition levels required to form a fix number of feature values, because the images sizes are not fixed and change from image to another .…”

Section: -Related Workmentioning

confidence: 99%

Analysis of Objects Information to Create Unique Features for Color Images

Alqadi¹,

Khrisat²

2020

IJCSMC

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Color digital images are widely circulated in various means of communication, and these images are used in multiple and vital applications, which forces us to search for easy and effective ways to represent the digital image with a set of unique values that facilitate the process of retrieving or recognizing the digital image. A digital image is mostly made up of a group of objects that can be used to generate a features vector for an image that can be used as an image identifier. In this paper, we will present a set of easy procedures through which it is possible to retrieve objects in a digital image and how to use the information of these objects toform the properties of the image. We will also demonstrate the flexibility of the presented procedures in using a wide range of object information to formulate unique image values that can be used as properties for digital image retrieval or recognition.

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“…In [10], a window method for an enhanced image [11][12][13][14][15][16][17] features extraction was proposed, this method is very simple and efficient but if the image was rotated the features will change, which will cost extra work and time to deal with process of identifying the image. In [18][19][20][21][22][23] deferent variants of algorithm were proposed, all of them are based on LBP and central symmetric LBP (CSLBP) operators, these methods create a unique feature for each image, but they are very sensitive to the image rotation. 2, but these features are very sensitive to the image position and if the image was rotated at least for 1 degree the features array will be changed accordingly as shown in Table 3, and this is the major disadvantage of this method.…”

Section: Related Workmentioning

confidence: 99%

A modified symmetric local binary pattern for image features extraction

Dwairi

2020

TELKOMNIKA

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The process of identifying images and patterns is one of the most important processes of digital image processing, which is used in many applications such as fingerprint recognition, face recognition and pattern recognition. Due to the large size of the image, the process of identifying the image requires a great time, which in turn leads us to extract some characteristics of the magnitude of the volume, which can be used as an identifier to retrieve the image or recognize it and thus we have devoted a lot of time to identify the image. In this research paper, a modified symmetric local binary pattern (MSLBP) method was proposed to extract texture features. The proposed algorithm was implemented on many digital fingerprint's images and the local structure features of these images were obtained. Several image recognition experiments are conducted on these features and compared with other algorithms. The results of the proposed algorithm showed that the digital image was represented in a very small size and furthermore the speed and accuracy of image recognition based on the proposed method was increased significantly. Unlike the methods based on LBP, the proposed method gives the same features of the image even if the image was rotated with any angle.

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A Novel Technique for Data Steganography

Cited by 18 publications

References 11 publications

Novel Ransomware Hiding Model Using HEVC Steganography Approach

Novel Ransomware Hiding Model Using HEVC Steganography Approach

Analysis of Objects Information to Create Unique Features for Color Images

A modified symmetric local binary pattern for image features extraction

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