Anomaly Detection Based Secure in – Network Aggregation for Wireless Sensor Networks

  IJRES-book-cover  International Journal of Recent Engineering Science (IJRES)         
© 2014 by IJRES Journal
Volume-1 Issue-4
Year of Publication : 2014
Authors : K.Rajesh
DOI : 10.14445/23497157/IJRES-V1I4P102

How to Cite?

K.Rajesh, "Anomaly Detection Based Secure in – Network Aggregation for Wireless Sensor Networks," International Journal of Recent Engineering Science, vol. 1, no. 4, pp. 6-10, 2014. Crossref,

Secure in-network aggregation in wireless sensor networks (WSNs) is a necessary and challenging task. This project first proposes integration of system monitoring modules and intrusion detection modules in the context of WSNs. And propose an extended Kalman filter (EKF) based mechanism to detect false injected data. Specifically, by monitoring behaviors of its neighbors and using EKF to predict their future states (actual in-network aggregated values), each node aims at setting up a normal range of the neighbors’ future transmitted aggregated values. This task is challenging because of potential high packet loss rate, harsh environment, and sensing uncertainty. The project illustrates how to use EKF to address this challenge to create effective local detection mechanisms. Using different aggregation functions (average, sum, max, and min), presents how to obtain a theoretical threshold. The project further applies an algorithm of combining cumulative summation and generalized likelihood ratio to increase detection sensitivity. To overcome the limitations of local detection mechanisms, it illustrates how The proposed local detection approaches work together with the system monitoring module to differentiate between malicious events and emergency events. The project simulates to evaluate local detection mechanisms under different aggregation functions.

Channel resolution, Garbage output, constant input, power consumption, omni-directional antenna.

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