Analysis of Secure In-Network Aggregation for Anomaly Detection in Wireless Sensor Networks
Secure in-network aggregation in wireless sensor networks is a necessary and challenging task. Secure in-network aggregation refers to acquiring the sensed data from the sensors and transmitting the sensed information to the gateway node. Integration of system monitoring modules and intrusion detection modules are proposed in WSN. An Invariant extended Kalman filter based mechanism is used to detect false injected data in case of non-linear systems possessing symmetries. This task is challenging because of potential high packet loss rate, harsh environment, and sensing uncertainty. The main objective of secure in-network aggregation is to reduce the packet loss rate and small power consumption. An algorithm for combining cumulative summation and generalized likelihood ratio is used to increase detection sensitivity. To overcome the limitations of local detection mechanisms, our proposed local detection approaches work together with the system monitoring module to differentiate between malicious events and emergency events.
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