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Recognition and Handling of Insider and Outsider DDOS Attacks in WSN
Objectives: Recognition and Handling of Insider and Outsider DDoS attacks are very important in WSN. Various schemes have been proposed in the past to fight against DDoS attacks in WSN. But they have either used a complex approach for recognizing the attack or they were not able to handle the attack efficiently after recognizing it. The presented method has followed a simplified and effective approach to recognize and handle the DDoS attack. Methods: In this paper two methods have been introduced, Authentication method is based upon a mathematical formula which is only known to legitimate nodes in the network. In data filtration method, each node in the network checks the input data volumes coming from other nodes against a threshold value to find the traffic abnormalities. Both these methods are simple and can be deployed at every node in the network. Findings: The results have been verified using the Network Simulator 2 (NS2) on various performance metrics i.e. throughput, delay, lost packets, energy consumption and PDR. It has been observed that fixing the threshold value results in recognition of attack at very early stages and blocking the communication with the attacker results in saving approx 56% energy of the network.. The threshold value can be decided as per the bandwidth usage that may vary in different applications. Improvements: The data filtration method can be enhanced in future by using historical methods so as to analyze and mitigate other severe attacks like blackhole and sinkhole attacks.
Authentication, Data Filtration, DDoS, NS2, Threshold, WSN.
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