A framework of secured and bio-inspired image steganography using chaotic encryption with genetic algorithm optimization (CEGAO)

The two key issues related to steganography techniques are, statistical undetectability and picture quality. Image steganography takes the advantage of limited power of Human Visual System (HVS). The proposed framework offers an approach of secure data hiding technique in digital images. Novel scheme presented encrypts meaningful secret data using nonlinear dynamics (chaos theory) before embedding into host or cover image. A basic LSB embedding method is used for encrypting data into cover image. Genetic Algorithm based pixel adjustment process is used to reduce the difference of error between the host image and its stego version with low distortions. The results of proposed scheme are compared with other steganographic algorithm using Peak Signal to Noise Ratio (PSNR) and Structural Similarity (SSIM) index, color frequency test and StirMark analysis

Steganography: a class of secure and robust algorithms

This research work presents a new class of non-blind information hiding algorithms that are stego-secure and robust. They are based on some finite domains iterations having the Devaney's topological chaos property. Thanks to a complete formalization of the approach we prove security against watermark-only attacks of a large class of steganographic algorithms. Finally a complete study of robustness is given in frequency DWT and DCT domains.Comment: Published in The Computer Journal special issue about steganograph