Securing the vast amount of data transmitted across networks is crucial for Internet of Things (IoT) applications. In this paper, we present a novel approach to image encryption using “Elementary Cellular Automata (ECA)” rule vectors, designed to enhance the security of image transmission in “Internet of Things (IoT)” applications. The proposed method leverages the inherent simplicity and parallel processing capabilities of ECAs to generate complex pseudorandom sequences, which serve as the basis for the encryption process. By selecting appropriate ECA rules, the algorithm ensures a high level of unpredictability and robustness against common cryptographic attacks. The encrypted images are evaluated using standard metrics such as “Mean Squared Error (MSE),” “Peak Signal-to-Noise Ratio (PSNR),” “Unified Average Changing Intensity (UACI),” and “Number of Pixels Change Rate (NPCR).” Experimental results demonstrate that the proposed method offers significant improvements in both security and performance when compared to existing encryption techniques. This secure and efficient encryption framework is particularly well-suited for IoT environments, ensuring the confidentiality and integrity of transmitted images in scenarios where sensitive data protection is of utmost importance.