AI Deep Learning Technique for Wireless Sensor Network DDoS Attack Detection

The Wireless Sensor Network, also called the WSN, and its applications in data collecting and related fields are expanding quickly. The sensor nodes in a network velocity, data collecting, and data visualization are compact and user-friendly. The application alongside information mapping are beneficial for several sectors and uses. Research has been conducted on the safety of Wireless Sensor Networks (WSNs) due to issues related to power, energy, bandwidth, communication, and fire hazards. The security of Wireless Sensor Networks (WSNs) also impedes the efficacy of robust security measures. Consequently, a robust instrument for security exists within networks. Nevertheless, conventional IDS regulations remain applicable. A denial service (DoS) event transpires in this context. This work has presented DoS ideas and the current literature on Dcs models. The models are specifically developed to address blocking, arranging, and attack vectors, providing a foundation for the creation of Intrusion Detection Systems (IDS). The advantages and merits of this technique, along with its evolution, will be addressed next.