DWT-LSB APPROACH FOR VIDEO STEGANOGRAPHY USING ARTIFICIAL NEURAL NETWORK

Abstract: An important role is played by Video Steganography in information security field. Video basically plays as a basic choice for hiding the data. It is efficient as well as successful embedding process for selecting the suitable pixel in the video frames for storing the secret data. The main objective of the Steganography is to conceal the very existence of the secret data. In this work, for the decomposition of the image, hybridization of DWT with LSB is being used to find the best bits from the cover video for embedding the secret data. For embedding the secret data for the generation of the best pixels, artificial intelligence technique is used and for classifying the suitable regions in the cover data, artificial neural network is used as a classifier. Basically, this work has focussed on the security by using the combination of decomposition technique with the machine learning methods for the enhancement of the security rate in the realistic applications. Parameters like PSNR, MSE and entropy are used to check the effective results being obtained after the execution of the simulation work. The proposed work has shown an improvement as compare to the existed work.

Keywords: Image Processing, Video Stagenography, DWT, ANN, LSB, PSNR, SD, MSE and entropy