Scalable and Highly Secured Image Steganography Based on Hopfield Chaotic Neural Network and Wavelet Transforms

Steganography is the science of communicating in the hidden manner. This paper presents a robust and secured Image Steganography method capable of embedding high volume of text information in digital cover-image without incurring any perceptual distortion. The method is based on compression and encryption. In order to achieve high capacity, dictionary based lossless compression techniques are used. And to achieve high security, encryption mechanism using Hopfield Chaotic Neural network is used. The message to be transmitted is compressed first using Lempel Ziv scheme technique and is encrypted by HCNN and then embedded into the image using Discrete Wavelet transforms. The proposed method is tested with different images and text of various lengths and found to be efficient, secure and has high embedding capacity.