A lightweight encryption algorithm for resource-constrained IoT devices using quantum and chaotic techniques with metaheuristic optimization.

As the internet of things (IoT) continues to proliferate, the need for efficient and secure data encryption has become increasingly critical, particularly for resource-constrained devices. Existing encryption methods offer adequate security for digital data; however, they often fall short when applied to resource-constrained IoT devices. This research introduces a novel lightweight encryption algorithm optimized with metaheuristic techniques, incorporating quantum encryption, confusion and diffusion operations, discrete wavelet transform (DWT), and multiple chaotic maps. Initially, a color image is decomposed into its three color components-red (R), green (G), and blue (B)-and then transformed into its quantum representation, where quantum encryption operations are performed. Following this, the quantum image is transformed back into a classical format to apply confusion and diffusion techniques. Confusion is achieved by generating a substitution matrix and applying a modular operation to introduce pixel-level confusion. A key matrix is then created to implement the diffusion operation. In the final phase, DWT is used to extract frequency sub-bands, forming a low-frequency sub-band and further extracting sub-bands up to the 4th level, which are substituted using values from the substitution box. The performance of the proposed encryption framework is evaluated through various statistical analyses, including entropy, correlation, key sensitivity, lossless analysis, and histogram analysis. The results demonstrate notable statistical measures with an entropy of 7.9998, a correlation of 0.0001, and a key space of [Formula: see text]. Additionally, the encryption's robustness is tested against several cyberattacks, such as noise, cropping, and brute force, showcasing its effectiveness in resisting these threats.