Improvised Secure data transfer through the use of steganography for IoT network node data security

The network of actual physical objects, or items having software, sensors, and other technology implanted in them The Internet of Things (IoT) is a network of interconnected devices and systems that communicate with each other via the Internet to share data. IoT devices should be secured even if many of them are publicly accessible to everyone on the network. This is because it is crucial to understand the security risks and the potential for cyberattacks. Data can be hidden using a method that involves using bits to represent successive rows in a picture file that have pixels of the same color. The result is a picture file that seems identical to the original but includes typical, unencrypted “noise” patterns data because the encrypted data was applied to this redundant data discretely. The goal of this project is to use picture data hiding to encrypt data from IoT networks by concealing the message within an image file. By using convolutional neural networks, the payload which can be conveyed via a visual will be significantly expanded in conjunction with the conventional picture data hiding approach. To get the maximum payload, various convolutional settings will be examined. The data will be encrypted and decrypted using the recently created deep learning algorithm. In order to improve the payloads of information to be encrypted and securely decrypted for displaying the original message, convolutional networks will be trained in this study.