Image Steganography Using Deep Neural Networks

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Reddy Madhavi K.1, PhD, K. Pranitha2, M. Tech, Nagendar Yamsani3, M. Tech, Mohmad Ahmed Ali4, M. Tech, K. Srujan Raju5, PhD and Balijapalli Prathyusha6, B. Tech
1School of Computing, Mohan Babu University, Tirupati, India
2B.V. Raju Institute of Technology, Narsapur, Medak, Telangana, India
3Assistant Professor, School of Computer Science and Artificial Intelligence, SR University, Warangal, India
4Associate Professor, Department of CSE, CMR Institute of Technology, Hyderabad, Telangana, India
5Professor, Department of CSE, CMR Technical Campus, Hyderabad, Telangana, India
6UG Scholar, CSE. Sree Vidyanikethan Engineering College, Tirupati, A.P., India

Part of the book: Information and Knowledge Systems
Chapter DOI: https://doi.org/10.52305/YKAF1880

Abstract

Steganography involves the use of hiding a secret or unknown message in a regular message. Steganography is commonly used in such a way that smaller messages are difficult to detect within a larger image’s noisy areas. In this chapter, we try to fit a color image in another image which is of the same size. Deep Neural Networks (DNN) are trained to simultaneously produce the concealing and disclosing activities in a pair-wise fashion. The system is tested on real-world photos from a range of sources and was trained on images chosen at random from the ImageNet collection. Beyond illustrating how deep learning may be used to successfully hide images, we closely study the process and consider extensions. Many methods such as Least Significant Bit (LSB), Highly Undetectable steGO (HUGO), Wavelet Obtained Weights (WOW) are effective for image steganography but they encrypt the secret message in the carrier image’s Least Significant Bits, in contrast to the Deep Neural Network method, which compacts and spreads the representation of the secret image throughout all of the available bits. Without being expressly instructed to do so, the deep neural network algorithm examines the data for features that correlate and combine them to support learning in a faster way. This is the most advanced technique which is used for the image steganography.

Keywords: steganography, LSB, HUGO, WOW, deep neural networks


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