An energy-efficient clustering and intrusion detection system (IDS) routing approach was developed for data transmission in a WSN. To transfer data in an energy-effective manner, the proposed approach utilizes a low-energy adaptive clustering hierarchy (LEACH); fuzzy logic and ANN classifiers were used for the IDS. Initially, the nodes were randomly placed in the network. LEACH then chooses the CHs at random and allocates this function to various nodes using a round-robin management program to ensure reasonable energy loss among nodes. Finally, intrusion detection procedures are launched to indicate the presence of intruders in the scheme. Within the WSN, Fuzzy interference was utilized to detach the nodes from legitimate nodes, and an ANN was utilized to separate the malicious nodes from suspicious nodes. The proposed classification model was tested using several metrics that achieved better performance, such as an accuracy of 97%, precision of 97%, error value of 0.03, specificity of 97%, sensitivity of 95%, F1_Score of 96%, FNR of 0.032, FPR of 0.025, and Kappa value of 94%. Thus, the LEACH and Fuzzy-based IDS approaches are the best for transmitting data in WSNs. In future work, advanced protocols will be used to efficiently transfer data, and an artificial intelligence model will be used to detect dead cluster heads to overcome the problems of corrupted and dead network paths .
Virtual Reality & Intelligent Hardware
Effective data transmission through energy-efficient clustering and Fuzzy-Based IDS routing approach in WSNs
28-Feb-2024