Robust Image Steganography Using Chaotic Logistic Maps: Embedding, Extraction, and Attack Resistance

This work presents a secure image steganography technique based on chaotic logistic maps to embed information into binary grayscale images. The proposed method utilizes the deterministic but non-predictive properties of chaotic systems in order to enhance data concealing and to make it more resistant to various attacks, including noise addition, JPEG compression, and cropping. We elucidate the mathematical representation of the chaotic logistic map, discuss the embedding and extraction algorithms, and assess the performance of the technique with PSNR and accuracy in data extraction. The results show the effectiveness of our approach in maintaining the integrity of the data and the quality of the images under various attack scenarios.