Research Article Open Access

Energy Efficient Error Detection in Data Aggregation in WSN

Abstract

Wireless sensor networks are vulnerable to many types of security attacks, including data forgery, false data injection and eavesdropping. Sensor nodes can be compromised by intruders and the compromise nodes can distort data integrity by injecting false data. The transmission of error data depletes the constrained battery power and degrades the bandwidth utilization. False data can be injected by compromised sensor nodes in various ways, including data aggregation and relay. In WSNs, data aggregation is performed by sensor nodes, called data aggregators. This project is to detect false data injected by a data aggregator while performing data aggregation. Data aggregation is implemented in WSNs to eliminate data redundancy, reduce the energy consumption and improve data accuracy. To support data aggregation along with false data detection, every node will be monitored along with Naïve Bayes Detector and Fuzzy logic model. By using two detectors we can find the fault data easily and increase the accuracy of the network.

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