Data Hiding in Image using Steganography

The increasing prevalence of data breaches and unauthorized access has heightened the need for secure communication methods. Image steganography, a branch of data hiding, provides an effective solution by embedding secret information into digital images without noticeable distortion. This study focuses on the Least Significant Bit (LSB) substitution technique due to its simplicity, efficiency, and high accuracy. In this approach, the LSBs of image pixels are replaced with secret data bits, producing stego-images that appear visually identical to the original. The methodology integrates preprocessing, embedding, and extraction processes, supported by libraries such as Pillow (PIL) and OpenCV for image handling. Experimental evaluation was conducted using metrics like Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index (SSIM), Mean Squared Error (MSE), and Bit Error Rate (BER) to assess imperceptibility, robustness, and payload capacity. Results demonstrate that the LSB method maintains image quality while enabling accurate data retrieval, achieving up to 92% accuracy. The work further highlights the role of reversible data hiding and explores resilience against steganalysis attacks. Overall, this study underscores LSB-based steganography as a practical and efficient technique for secure data transmission, with potential applications in domains such as digital forensics, healthcare, and defense.