A Lightweight Chaos-Based RGB Image Encryption Scheme for IoT Using Dynamic Diagonal Strip Permutation and XOR Diffusion

Internet of Things (IoT) devices have found applications in numerous areas, including smart homes, health- care monitoring, smart metering, waste management, and industrial systems. These devices frequently collect and transmit data to fog nodes or cloud platforms for further processing. Ensuring the security of such data remains challenging, particularly when resource-constrained devices are involved. This paper presents a lightweight chaos-based image encryption scheme based on a two-stage confusion–diffusion structure. The proposed method employs the three-dimensional Intertwining Logistic Map (ILM) to gener- ate chaotic sequences that control the encryption operations. In the confusion stage, the input RGB image is decomposed into its red, green, and blue components, from which two color components are dynam- ically selected according to the generated chaotic sequences. Diagonal strips of varying positions and directions are then repeatedly exchanged between the selected components to disrupt both the spatial ar- rangement and cross-channel distribution of the image pixels. In the diffusion stage, a chaos-generated mask is combined with the scrambled image through bitwise XOR operations to modify the pixel intensities while maintaining computational simplicity. The proposed scheme is evaluated through a range of statis- tical and security analyses. Experimental results yield an average information entropy of 7.9975, close to the ideal value of 8 for an 8-bit image, while an average encryption time of 0.4269 seconds is obtained under the specified conventional computing environment. These results demonstrate the effectiveness and computational feasibility of the proposed approach and indicate its potential for resource-conscious image security applications. Validation on resource-constrained IoT and embedded platforms remains an impor- tant direction for future investigation.