In the era of Industrial IoT (IIoT) and Industry 4.0, ensuring secure data
transmission has become a critical concern. Among other data types, images are
widely transmitted and utilized across various IIoT applications, ranging from
sensor-generated visual data and real-time remote monitoring to quality control
in production lines. The encryption of these images is essential for
maintaining operational integrity, data confidentiality, and seamless
integration with analytics platforms. This paper addresses these critical
concerns by proposing a robust image encryption algorithm tailored for IIoT and
Cyber-Physical Systems (CPS). The algorithm combines Rule-30 cellular automata
with chaotic scrambling and substitution. The Rule 30 cellular automata serves
as an efficient mechanism for generating pseudo-random sequences that enable
fast encryption and decryption cycles suitable for real-time sensor data in
industrial settings. Most importantly, it induces non-linearity in the
encryption algorithm. Furthermore, to increase the chaotic range and keyspace
of the algorithm, which is vital for security in distributed industrial
networks, a hybrid chaotic map, i.e., logistic-sine map is utilized. Extensive
security analysis has been carried out to validate the efficacy of the proposed
algorithm. Results indicate that our algorithm achieves close-to-ideal values,
with an entropy of 7.99 and a correlation of 0.002. This enhances the
algorithm's resilience against potential cyber-attacks in the industrial
domain