Biblio

WSN is a collection of tiny nodes that used to absorb the natural phenomenon from the operational environment and send it to the control station to extract the useful information. In most of the Existing Systems, the assumption is that the operational environment of the sensor nodes deployed is trustworthy and secure by means of some cryptographic operations and existing trust model. But in the reality it is not the case. Most of the existing systems lacks in providing reliable security to the sensor nodes. To overcome the above problem, in this paper, Beta Reputation and Direct Trust Model (BRDT) is the combination of Direct Trust and Beta Reputation Trust for secure communication in Wireless Sensor Networks. This model is used to perform secure routing in WSN. Overall, the method provides an efficient trust in WSN compared to existing methods.

In wireless networks, spoofing attack is one of the most common and challenging attacks. Due to these attacks the overall network performance would be degraded. In this paper, a medoid based clustering approach has been proposed to detect a multiple spoofing attacks in wireless networks. In addition, a Enhanced Partitioning Around Medoid (EPAM) with average silhouette has been integrated with the clustering mechanism to detect a multiple spoofing attacks with a higher accuracy rate. Based on the proposed method, the received signal strength based clustering approach has been adopted for medoid clustering for detection of attacks. In order to prevent the multiple spoofing attacks, dynamic MAC address allocation scheme using MD5 hashing technique is implemented. The experimental results shows, the proposed method can detect spoofing attacks with high accuracy rate and prevent the attacks. Thus the overall network performance is improved with high accuracy rate.