Paper Contents
Abstract
The Internet of Things (IoT) describes the network of physical objects or things that are embedded with sensors, software, and other technologies for the purpose of connecting and exchanging data with other devices and systems over the internet. Although several IoT devices are openly accessible to all in the network, it is extremely vital to be aware of the security risks and threats of cyber-attacks; therefore, it should be secured. In Cryptography, plain text is converted to encrypted text before it is sent, and it is converted to plain text after communication on the other side. Steganography is a method of hiding secret data, by embedding it into an audio, video, image, or text file. One technique is to hide data in bits that represent the same colour pixels repeated in a row in an image file. By applying the encrypted data to this redundant data in some inconspicuous way, the result will be an image file that appears identical to the original image but that has "noise" patterns of regular, unencrypted data. In this project it proposes to encrypt the IoT networks data by hiding the message inside an image file using image data hiding technique. We are going to incorporate the usage of convolutional neural networks in traditional image data hiding method to drastically increase the payload that can be transmitted through an image. Different convolutional parameters will be analysed to achieve the highest payload. Encryption and decryption of the data will be performed using the newly developed deep learning algorithm. Thus, in this project the convolutional networks will be trained in such a way to increase the payload of the data to be encrypted as well as safely decrypted to view the original message.
Copyright
Copyright © 2023 I. Sujiban. This is an open access article distributed under the Creative Commons Attribution License.
