Abstract: Wireless Sensor Networks are often deployed in unfavourable situations where an assailant can physically capture some of the nodes, first for reprogram the node and then, it occurs replicate them in a large number of clones, easily taking control over the network. This replication node is also called the Clone node. The clone node behaves as a legitimate node or original node. In node replication attack detecting the clone node important issue in Wireless Sensor Networks. A few distributed solutions have been recently proposed, but they are not satisfactory .First, they are energy and memory demanding: A serous drawback for any protocol to be used in the WSN-resource compactness environment. In this project first investigate the selection criteria of clone detection schemes with regard to device type, detection methodologies, deployment strategies, and detection ranges. Further, they are vulnerable to the specific assailant models introduced in this paper. The contributions of this work are threefold. First analyze the desirable properties of a distributed mechanism for the detection of node replication attacks. Second show that the known solutions for this problem do not completely meet our requirements. Third it may consist of sequential probability ratio test protocol using for this algorithm to identify the detection of node replication attacks, and show that it satisfies the introduced requirements. Our implementation specifies, user will specify its ID that means client id, secret key will be create, and then include the port number. The witness node will verify the internally bounded user id and secret key. The witness node means original node. If the verification is success, the information collecting to the packets that packets are send to the destination.
Keywords: Static WSNs, Distributed mechanism, Node replication Attacks, Sequential probability ratio test.
Title: Detecting the Node Replication Attacks in Wireless Sensor Networks
Author: K. Anitha, A. Senthil Kumar
International Journal of Computer Science and Information Technology Research
ISSN 2348-1196 (print), ISSN 2348-120X (online)
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