Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Insights into Artificial Neural Network techniques, and its Application in Steganography Subject The topic of the resource Convolution Neural Networks; Deep Steganography; Feed forward; LSTM; Optimization Algorithms; Recurrent Neural network Description An account of the resource Deep Steganography is a data concealment technology that uses artificial intelligence (AI) to automate the process of hiding and extracting information through layers of training. It enables for the automated generation of a cover depending on the concealed message. Previously, the technique depended on the existing cover to hide data, which limited the number of Steganographic characteristics available. Artificial intelligence and deep learning techniques have been used to steganography recently and the results are satisfactory. Although neural networks have demonstrated their ability to imitate human talents, it is still too early to draw comparisons between people and them. To improve their capabilities, neural networks are being employed in a number of disciplines, including steganography. Recurrent Neural Networks (RNN) is a widely used technology that automatically creates Stego-text regardless of payload volume. The features are extracted using a convolution neural network (CNN) based on the image. Perceptron, Multi-Layer Perceptron (MLP), Feed Forward Neural Network, Long Short Term Memory (LSTM) networks, and others are examples of this. In this research, we looked at all of the neural network approaches for Steganographic purposes in depth. This article also discusses the problems that each technology faces, as well as potential solutions. 2021 Institute of Physics Publishing. All rights reserved. Creator An entity primarily responsible for making the resource Gurunath R.; Samanta D. Source A related resource from which the described resource is derived Journal of Physics: Conference Series, Vol-2089, No. 1 Publisher An entity responsible for making the resource available IOP Publishing Ltd Date A point or period of time associated with an event in the lifecycle of the resource 2021-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1088/1742-6596/2089/1/012043" target="_blank" rel="noreferrer noopener">https://doi.org/10.1088/1742-6596/2089/1/012043</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121519081&amp;doi=10.1088%2F1742-6596%2F2089%2F1%2F012043&amp;partnerID=40&amp;md5=a940899a4d0d8d0d4623fd48aeb5708a" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121519081&amp;doi=10.1088%2f1742-6596%2f2089%2f1%2f012043&amp;partnerID=40&amp;md5=a940899a4d0d8d0d4623fd48aeb5708a</a> Rights Information about rights held in and over the resource All Open Access; Gold Open Access Relation A related resource ISSN: 17426588 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Gurunath R., Department of Computer Science, CHRIST University, Bangalore, India; Samanta D., Department of Computer Science, CHRIST University, Bangalore, India