Enhancemet of Network Security in Mobile Adhoc Networks using USASFO Algorithm for IoT Applications

The integration of Mobile Ad-hoc Networks (MANETs) in the Industrial Internet of Things (IIoT) facilitates decentralized communication between smart devices, offering flexibility for diverse applications such as law enforcement, military, disaster relief, and search and rescue operations. This paper introduces a lightweight key frame extraction method for efficient and secure data encryption in MANET-based IoT systems. To enhance data confidentiality, an unpredictable map-based cryptographic approach is proposed, optimizing encryption and decryption processes while preventing data loss. Furthermore, a novel security protocol, termed the Updated Self Adaptive Sail Fish Optimization (USASFO) algorithm, is developed to improve key generation and overall system security. Comparative analysis of optimization algorithms—MSFO, CHHSO, and USASFO—revealed that USASFO consistently outperformed the others, maintaining higher accuracy over multiple iterations. The proposed USASFO model not only enhances privacy preservation through chaotic cryptography but also ensures improved performance in securing MANET-based IIoT applications.