2022
DOI: 10.32604/cmc.2022.018631
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Novel Ransomware Hiding Model Using HEVC Steganography Approach

Abstract: 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… Show more

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Cited by 7 publications
(3 citation statements)
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“…To further ensure the superiority of the proposed crypto-steganography approach, we compared its accomplishment with recent related steganography algorithms that are introduced in [ 38 , 39 , 58 ]. These introduced algorithms are based on only one stage of LSB steganography without employing further security stages like encryption or random embedding strategy as investigated in our proposed work in this paper.…”
Section: Results and Comparisonsmentioning
confidence: 99%
See 1 more Smart Citation
“…To further ensure the superiority of the proposed crypto-steganography approach, we compared its accomplishment with recent related steganography algorithms that are introduced in [ 38 , 39 , 58 ]. These introduced algorithms are based on only one stage of LSB steganography without employing further security stages like encryption or random embedding strategy as investigated in our proposed work in this paper.…”
Section: Results and Comparisonsmentioning
confidence: 99%
“…These introduced algorithms are based on only one stage of LSB steganography without employing further security stages like encryption or random embedding strategy as investigated in our proposed work in this paper. Table 7 shows the objective outcomes of the comparative analysis between the proposed approach compared to the related algorithms [ 38 , 39 , 58 ] in terms of all quality assessment metrics that were presented in Table 3 .…”
Section: Results and Comparisonsmentioning
confidence: 99%
“…Figure of merit PSNR is calculated using the mean-square error between the original and filtered images. The proposed truncated approximation multiplier is compared with various previous [22,[27][28][29][30], multipliers to validate the quality through the errors. Testing of the proposed is performed with sharpening and JPEG compression image processing applications.…”
Section: Normalized Mean Error Distance (Nmed)mentioning
confidence: 99%