An Effective Classification for DoS Attacks in Wireless Sensor Networks

Intrusion Detection Systems (IDSs) have an important role in detecting and preventing security attacks. An IDS should be in Wireless Sensor Networks (WSN) to ensure the security and dependability of WSN service. In this paper, we present an approach method to detect types of DoS attacks in WSN. In particular, we apply Random Forest model to detect type of DoS attacks on WSN-DS dataset. The proposed approach achieves the best performance with F1-score of attacks are 99%, 96%, 98%, 100%, and 96% for Blackhole, Flooding, Grayhole, Normal, and Scheduling (TDMA) attacks, respectively.