In WSN the computational power of very low power processors dramatically increases, mostly driven by demands of mobile computing. When the cost of such technology drops, WSNs will be able to afford hardware which can implement more sophisticated data aggregation and trust assessment algorithms. The aggregation of data from multiple sensor nodes is done at the aggregating node, by simple method such as averaging to overcome the limited computational power and energy resources in WSN. However such aggregation is known to be highly vulnerable to node compromising attacks. Generally, WSNs are highly susceptible to such attacks due to absences of tamper resistant hardware. Iterative Filtering technique simultaneously aggregate data from multiple sources, usually in a form of corresponding weight factors. Iterative Filtering is introduced which are more robust against collusion attacks than the simple averaging methods. It is not only collusion robust but also more accurate and faster converging.
Wireless sensor network, Robust data aggregation, Collusion attack
