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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM3171
Volume:
4 |
3 |
Mar 2020
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
In the digital age, safeguarding sensitive information is paramount. This project, “Video Steganography Using Machine Learning with Python,” introduces an innovative method to conceal one video within another, secured by dual authentication. Users submit a “cover video,” a “hide video,” a unique password, and an audio clip for validation. Utilizing Convolutional Neural Networks (CNNs), the approach seamlessly embeds the hide video into the cover video by leveraging CNNs’ capability to analyze spatial relationships in visual data. Recovery of the hidden video requires the correct password and audio clip, ensuring robust security. This method advances data protection through cutting-edge machine learning techniques.
KEYWORDS
Publication Date
12/23/2024
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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No funding information available for this research.
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