Efficient steganalysis using convolutional auto encoder network to ensure original image quality.

ABSTRACT: Steganalysis is the process of analyzing and predicting the presence of hidden information in images. Steganalysis would be most useful to predict whether the received images contain useful information. However, it is more difficult to predict the hidden information in images which is computationally difficult. In the existing research method, this is resolved by introducing the deep learning approach which attempts to perform steganalysis tasks in effectively. However, this research method does not concentrate the noises present in the images. It might increase the computational overhead where the error cost adjustment would require more iteration. This is resolved in the proposed research technique by introducing the novel research method called Non-Gaussian Noise Aware Auto Encoder Conv

SUBMITTER: Ayaluri MR 

PROVIDER: S-EPMC7959617 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature