Title: Advanced intelligent data hiding using video stego and hybrid convolutional neural networks

Authors: Ravi Kumar

Addresses: Department of ECE, Jaypee University of Engineering and Technology, Guna, 473226., Madhya Pradesh, India

Abstract: The practice of steganography involves the concealment of confidential data inside other, seemingly innocuous files of the same or other sorts. The objective of this study is to create a stego technique that, when applied to a video clip, will successfully conceal a message inside its graphics. A model is developed for video steganography by developing a model to conceal video inside another video using hybrid convolutional neural networks (HyCNN). The second objective is to expand the size of the space that can be used for hiding, which has been accomplished via the use of CNN. The suggested model was trained using HyCNN on arbitrary pictures drawn from the ImageNet database. The findings also show that the system is able to produce excellent results in visibility and attacks, where the suggested approach is able to effectively mislead both the observer and the steganalysis software.

Keywords: convolutional neural networks; hiding data; image stego; steganography; video stego.

DOI: 10.1504/IJESDF.2026.150189

International Journal of Electronic Security and Digital Forensics, 2026 Vol.18 No.1, pp.69 - 80

Received: 27 Aug 2023
Accepted: 26 Oct 2023
Published online: 03 Dec 2025 *

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