Adaptive crypto-steganosystem for videos based on information content and visual perception

Steganography is the art of hiding secret data inside a carrier media. Most steganographic techniques suffer from the drawback that they are unable to retain the perceptual quality. Using saliency cues for developing an adaptive steganographic technique can help to alleviate this problem. In this work, a novel perception driven robust crypto-steganographic algorithm is proposed for embedding secure data in videos. The proposed scheme selects the payload regions based on natural scene statistics. To further strengthen the scheme and ensure intractability of secure data, the encrypted secret data is embedded in a random manner using jumbling sequence generator in the frames. We utilize perceptual hashing to evaluate the number of bit insertions that will not compromise the perceptual quality. A comprehensive performance evaluation of the proposed scheme is provided to detail the effectiveness. We demonstrate that the scheme shows a lot of promise in being robust against statistical and saliency based attacks.