EnSKM-FTOPSIS: Enhanced Secure Key Management Framework in Dynamic Mobile Wireless Sensor Networks

Applications for WSN are numerous and include medical status monitoring, military sensing and tracking, and traffic flow monitoring, where sensory devices are frequently moving between different sites. An appropriate encryption key protocol is needed to secure data and connections. The energy, memory, transmission range, communication, and processing capacity of the sensor nodes are severely limited. Energy is considered to be a significant influence in extending the network's lifetime when compared to all of these other resources. Key management is one tactic for preserving these networks' security. For secure communication in dynamic WSNs with node mobility, this article suggests an Enhanced Secure Key Management (EnSKM) Framework. The proposed network model is a WSN that is heterogeneous and hierarchical and consists of a base station, cluster-head nodes, and several mobile sensor nodes. The Improved K-Means Algorithm is used to cluster the mobile sensor nodes. A CH is in charge of each cluster and has the ability to broadcast messages to other clusters as well as to all of the sensors inside the clusters. The best node is chosen as the CH using a novel metaheuristic optimization approach called Red Panda Optimization. The suggested system uses a hybrid fuzzy TOPSIS decision-making approach for both creation of path keys and addition of additional nodes to the network. It improved the efficiency of the proposed system and since it reduces energy consumption, it also elongates the network lifetime. The proposed Selfish Herd Optimization combined with ElGamal (SH-mEEG) encryption technique and modified elliptic curve cryptography improves network security. By eliminating cryptanalyzed nodes, the network's security is improved and its resilience to cryptanalysis attacks is increased. The suggested method is implemented on NS2 platform and contrasted with alternative key management methods. The proposed model achieves lowest encryption time of 2.654 s, decryption time of 2.773 s, and highest security level with 98.372% when compared to existing approaches. These results demonstrate how the proposed EnSKM framework can improve security and efficiency in dynamic WSN setups.