Abstract
Wireless Sensor Network (WSN) is an important piece of infrastructure that is in great demand and rapidly expanding in various industries, including environmental monitoring and military. WSNs consist of numerous nodes, each of which functions as a sensor whose purpose is to collect data. The nodes operate under constraints and are susceptible to various attacks, due to weak network security the entire WSN can be affected. Recognizing the key role of WSN security, in recent years there has been a marked increase in the number of publications on the use of machine learning techniques for intrusion detection. In the presented work, we examine the application of WSNs in various military operations and propose an integrated approach to detect and neutralize attacks in network traffic. The main contributions of the study include classification of WSN applications in military field, development of methods to enhance network security, and identification of key areas for further research. The proposed model helps to improve the overall network security. At the same time, the research process has identified a number of open questions for future directions of work.