Mathematical Modeling in Color Difference Analysis in Consecutive Video Frames for Steganography

This study investigates spatial domain video steganography, driven by the increasing demand for secure data embedding techniques that leverage inherent video properties to remain undetectable. Traditional approaches in the literature often neglect the detailed statistical characterization of naturally occurring pixel color differences across video frames, creating a significant gap in understanding how these variations can be systematically analyzed and effectively applied to steganographic methods. To address this deficiency, the study develops a comprehensive mathematical model for video files, introducing a function to compute inter-frame color differences and constructing a formalized color difference histogram. This innovative metric enables precise characterization of video files by analyzing the frequency and distribution of pixel color variations, offering a novel perspective on video content analysis. The findings confirm that the proposed model reliably captures the statistical patterns of color differences, providing a robust and scalable framework for improving steganographic techniques. By leveraging these patterns, the model enhances the resilience and imperceptibility of spatial domain steganography against detection and tampering. Future research will extend this framework to diverse video datasets, exploring its adaptability and uncovering additional insights into natural color variation dynamics and their potential applications in secure information encoding. This work lays the foundation for further advancements in the integration of statistical analysis and steganographic innovation.