Virtual Jamming Attacks Detection Using Neural Networks

Wireless Sensor Networks (WSNs), in recent times, have become one of the most promising network solutions with a wide range of applications in agriculture, health and military environments. Despite these promising applications, sensor nodes in WSN are vulnerable to security attacks, one of which is virtual jamming. The goal of this report is to develop a system that can protect data from virtual jamming attacks using neural networks technology. To evaluate the performance of the proposed system, the confusion matrix is used as the main evaluation tool. The confusion matrix will make it possible to measure the extent to which the system is able to distinguish between normal conditions and virtual jamming attacks. Evaluation of the level of detection accuracy, precision, recall, and F1 value is carried out to provide an in- depth understanding of the effectiveness of the system.