Lightweight encryption mechanism with discrete-time chaotic maps for Internet of Robotic Things

Chaotic systems have different characteristics that can be utilized for the purpose of cyber security. These features result from the erratic structure of images, making it difficult for systems to comprehend those images. Therefore, chaotic systems can serve as an effective means of securely storing and concealing images by implementing them in the IoRT for data encryption. In this study, a new lightweight encryption mechanism for IoRT based robots is proposed. A novel chaotic encryption mechanism is designed with discrete-time chaotic maps (Cubic Map and Ricker's Population Model Map) for more efficiently encrypting large-sized data, such as images and videos, in robots. The test of the developed mechanism was conducted on the NVIDIA Jetson Orin development kit, which is utilized in artificial intelligence-supported robots and boasts high performance and energy efficiency. The study's most important finding is that the established mechanism is suitable for parallel processing, making it possible to accomplish a high rate of image encryption per second utilizing the proposed method. In order to encrypt large files for IoRT, firstly, random number generation was performed and statistical tests were carried out. Then, encryption operations were performed with the developed encryption algorithm and security analyses were realized. The performances of the proposed mechanism will be compared with some studies in the literature. Based on the obtained image analysis and encryption performance, it has been shown that the developed mechanism can be easily used with high security for IoRT.