Abstract
Hiding Data and Detecting Hidden Data in Raw Video Components Using SIFT Points
Highlights
Steganography, which is a Greek word meaning covering writing [1], is an important sub-discipline of datahiding methods, which involves the process of hiding data in a medium
The results indicate that the proposed steganography method is effective because it yields higher peak signal-to-noise ratio (PSNR = 95.41 dB) compared to other techniques described in cybersecurity literature, and Convolutional Neural Networks (CNN) cannot detect hidden data with much success due to its 52% accuracy rate
Videos are taken in real time to detect the highest quality Scale Invariant Feature Transform (SIFT) keypoints of each frame dynamically
Summary
Steganography, which is a Greek word meaning covering writing [1], is an important sub-discipline of datahiding methods, which involves the process of hiding data in a medium. These media components may be a picture, an audio, a video, a web page, and such. This technique is usually employed by illegal groups who want to disseminate information online in an untraceable way. The most important difference between steganography and cryptography is that the former is able to detect whether there is meaningful data in the target object. In short steganography is described as "the art of hiding data" [2]
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