A wireless network with the advantages of sensing and processing information is referred to as a Wireless Sensor Network (WSN). It consists of a small sensor node with sensors, a battery, a microprocessor and a storage medium. It is an economical and simple solution for a variety of applications. The openness of wireless sensor networks makes it impossible to cope with various security threats. Several security attacks, black holes, wormhole attacks, DDOS attacks, etc., can jeopardize information and sensor nodes in the network. Distributed Denial of Service (DDoS) attacks are such attacks, the purpose of which is to destroy the network by exhausting resources. Attackers not only send worthless messages to increase network traffic, but also reduce the life of nodes and networks. In WSN, the lifetime of the network is proportional to the battery capacity. Therefore, depleting battery power directly reduces the life of the node. This research work has deal with the mitigation and prevention of DDoS attack by using Artificial Neural Network (ANN) as a classification algorithm. The simulation has been done in CLOUDSIM environment. The main of the work is to lessen the strength of attack with its prevention from reaching it to the victim with the anomaly detection system with the algorithm being proposed. Parameters, such as energy consumption, delay and PDR (packet delivery ratio) has been considered for the evaluation of the proposed

WSN (Wireless sensor network), DDoS (Distributed Denial of service), CLOUDSIM, Energy consumption

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