QR DWT Guided Steganography Using Machine Learning
Manikanta Prasad J, H B Pramod · 2024
Steganography is the practice of concealing a message, image, or file within another message, image, or file in a way that is not readily apparent to observers. Unlike cryptography, which focuses on making a message unreadable to unauthorized parties, steganography aims to hide the existence of the communication itself. In this study, we offer a revolutionary steganography method that combines machine learning approaches, Quick Response (QR) codes, and Discrete Wavelet Transform (DWT). The integration of DWT allows for efficient decomposition of images into frequency bands, enabling the hiding of information in the least significant bits of wavelet coefficients. QR codes serve as carriers for the hidden data, providing a recognizable format for embedding and extraction. Furthermore, machine learning algorithms are employed to optimize embedding locations within the image, enhance the robustness of the steganographic scheme against detection, and improve overall performance. The proposed method offers a sophisticated and secure means of concealing sensitive information within images, making it suitable for applications where privacy and confidentiality are paramount. Experimental results demonstrate the effectiveness and efficiency of the QR DWT guided steganography using machine learning, highlighting its potential in secure communication scenarios.