Open Access

ARTICLE

Optimizing Region of Interest Selection for Effective Embedding in Video Steganography Based on Genetic Algorithms

Nizheen A. Ali¹, Ramadhan J. Mstafa^2,3,*

1 Department of Computer Science, College of Science, University of Duhok, Duhok, 42001, Iraq
2 Department of Computer Science, Faculty of Science, University of Zakho, Zakho, 42002, Iraq
3 Department of Computer Science, College of Science, Nawroz University, Duhok, 42001, Iraq

* Corresponding Author: Ramadhan J. Mstafa. Email:

Computer Systems Science and Engineering 2023, 47(2), 1451-1469. https://doi.org/10.32604/csse.2023.039957

Received 26 February 2023; Accepted 20 April 2023; Issue published 28 July 2023

Abstract

With the widespread use of the internet, there is an increasing need to ensure the security and privacy of transmitted data. This has led to an intensified focus on the study of video steganography, which is a technique that hides data within a video cover to avoid detection. The effectiveness of any steganography method depends on its ability to embed data without altering the original video’s quality while maintaining high efficiency. This paper proposes a new method to video steganography, which involves utilizing a Genetic Algorithm (GA) for identifying the Region of Interest (ROI) in the cover video. The ROI is the area in the video that is the most suitable for data embedding. The secret data is encrypted using the Advanced Encryption Standard (AES), which is a widely accepted encryption standard, before being embedded into the cover video, utilizing up to 10% of the cover video. This process ensures the security and confidentiality of the embedded data. The performance metrics for assessing the proposed method are the Peak Signal-to-Noise Ratio (PSNR) and the encoding and decoding time. The results show that the proposed method has a high embedding capacity and efficiency, with a PSNR ranging between 64 and 75 dBs, which indicates that the embedded data is almost indistinguishable from the original video. Additionally, the method can encode and decode data quickly, making it efficient for real-time applications.

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Keywords

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