StegoMos: A secure novel approach of high rate data hidden using mosaic image and ANN-BMP cryptosystem

This paper discusses a secure novel approach of high rate data hidden using mosaic image and bitmap (bmp) cryptosystem. The mosaic image used in this approach together with the neural cryptosystem that have been implemented for the first time and has been successful, this new method of hiding data is based on LSB in mosaic images. A mosaic is an image that is comprised of hundreds or thousands of other images to create one common image. The proposed approach is named “StegoMos”. Once the mosaic cover is chosen, then data is secured by the crypto-system which is used to encrypt the data before hiding. The crypto-system is based on BAM neural network. The importance of neural networks in this work is that they offer a very powerful and a very general framework for representing non-linear mapping from several input variables to several output variables. Merging high rate data hiding in mosaic images as well as making the data secure arises from the requirements of the problem of increasing the amount of data hidden and at the same time maintains the quality of image. The second requirement is the security of data. Experimental results show the effectiveness of using the mosaic image cover over the normal image.