Enhancing privacy in data transmission between IoT devices: A robust encryption and embedding framework for secure and meaningful image communication

Abstract

Image transmission between IoT devices has increased significantly, raising privacy concerns due to the unsecured nature of the internet. Researchers are exploring encryption schemes to protect IoT-transmitted data from unauthorized access. Most image encryption schemes produce noisy and random images. However, attackers pay particular attention to images that seem random or like noise and, as a result, these images are susceptible to cyberattacks. In this research, a new encryption framework is designed to transform plaintext images into meaningful representations while maintaining a high level of security. The proposed framework comprises two key processes: (a) the encryption process and (b) the embedding process. In the encryption stage, a plaintext color image undergoes encryption using four main components: (i) multiple chaotic maps, (ii) a confusion operation, (iii) a bit-plane extraction method, and (iv) a diffusion operation. Following the encryption of the plaintext color image, the embedding process begins to generate the meaningful image corresponding to the original color image. For the embedding process, the discrete wavelet transform is employed to extract frequency bands (e.g., Low-Low (LL), Low-High (LH), High-Low (HL), and High-High (HH)) from a mask image containing non-essential information. Once these frequency sub-bands are extracted, the pixels of the encrypted image are divided into two groups, such as the least significant bits (LSBs) and the most significant bits (MSBs). These two groups are then replaced with the HL and HH sub-bands of the mask image. Subsequently, the inverse discrete wavelet transform is applied to the unchanged LL and LH sub-bands, and the sub-bands are replaced with LSBs and MSBs to produce a meaningful image. To assess the effectiveness of the proposed framework, various security analyses, including key space analysis, key sensitivity analysis, histogram analysis, structural similarity index measure (SSIM), entropy, correlation, energy, and computational time analysis, are conducted. The proposed framework exhibited exceptional security for digital images, with exceptional values for correlation, entropy, contrast, SSIM, and computational time analysis measured at −0.0004, 7.9995, 10.7291, 0.0084, and 0.0018 s, respectively. Furthermore, a noise attack was executed on the encrypted image generated by the proposed encryption framework, demonstrating its resilience against such attacks.

Keywords: Chaos, Cybersecurity, Discrete wavelet transform, Internet of Things, Meaningful encryption