Improved Steganography for IoT Network Node Data Security Promoting Secure Data Transmission using Generative Adversarial Networks

Abstract

An internet of things (IoT) is an intelligent environment such as homes and smart cities of our country, and IoT improves the new technology implementation for home automation. The problem with security in IoT-based devices is that data transmission and signal passing are easily hacked using encryption and decryption methods. The old technology of the Steganography method does not improve the data hidden in images because encryption and decryption use a 1-bit 0.05-bit store, and low ranges hide the information in images, so that information hides out of the size and bits of the image. The hackers easily hack the hide information pixel by pixel or bit by bit in images. So, need for a proposed system, new technology, or methods. The suggested solution improves data concealment in photos by combining CNN’s deep learning techniques with steganography. The secret information these photographs convey can be shared without drawing hackers’ notice. The data is encrypted before being embedded in the image to increase its security. Steganography messages are frequently encrypted using more conventional methods first, after which the encrypted message is added to the cover image in some manner. The previous algorithm of SFNET algorithm architecture has been divided by segment, the segment based on width, height, and depth changes based improve performances. Existing systems of SFNET and SRNET are compared to the fractal net algorithm to improve the performance of 3 to 1 % of the proposed system.