Abstract
Rapid advancements of the Industrial Internet of Things (IIoT) and artificial intelligence (AI) pose serious security issues by revealing secret data. Therefore, security data becomes a crucial issue in IIoT communication where secrecy needs to be guaranteed in real time. Practically, AI techniques can be utilized to design image steganographic techniques in IIoT. In addition, encryption techniques act as an important role to save the actual information generated from the IIoT devices to avoid unauthorized access. In order to accomplish secure data transmission in IIoT environment, this study presents novel encryption with image steganography based data hiding technique (EIS-DHT) for IIoT environment. The proposed EIS-DHT technique involves a new quantum black widow optimization (QBWO) to competently choose the pixel values for hiding secrete data in the cover image. In addition, the multi-level discrete wavelet transform (DWT) based transformation process takes place. Besides, the secret image is divided into three R, G, and B bands which are then individually encrypted using Blowfish, Twofish, and Lorenz Hyperchaotic System. At last, the stego image gets generated by placing the encrypted images into the optimum pixel locations of the cover image. In order to validate the enhanced data hiding performance of the EIS-DHT technique, a set of simulation analyses take place and the results are inspected interms of different measures. The experimental outcomes stated the supremacy of the EIS-DHT technique over the other existing techniques and ensure maximum security.
Highlights
Industry 4.0 is the 4th generation industrial revolution that has dramatically increased from the Internet of Things (IoT) to the industrial IoT (IIoT)
This study presents novel encryption with image steganography based data hiding technique (EISDHT) for IIoT environment
For examining the improved data hiding performance of the EIS-DHT technique, a set of experimentation were carried out and the results are examined based on distinct metrics
Summary
Industry 4.0 is the 4th generation industrial revolution that has dramatically increased from the Internet of Things (IoT) to the industrial IoT (IIoT). Horng et al [17] proposed an interpolation-based reversible data hiding (IRDH) system which enhances Lee and Huang’s scheme and Malik et al.’s system by integrating its embedding methods and the optimal pixel adjustment process (OPAP) rises the embedding capability and the visual quality of the systems. In this proposed work, they begin by stretching the size of the original image with the present enhanced neighbor mean interpolation (ENMI) interpolation approach later the data is embedded to the interpolated pixel with this new embedding technique which is based on the intensity of the pixel and the maximized variance value. For examining the improved data hiding performance of the EIS-DHT technique, a set of experimentation were carried out and the results are examined based on distinct metrics
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