Iterative Filtering Algorithm Based on Robust Data Aggregation Method for Wireless Sensor Network in the Presence of Adversary Environment

As we have limited computational power and energy resources ,aggregation of data from the multiple sensor node is done at the aggregator node is usually accomplished by simple method is averaging. WSNs are usually unattended and without tamper resistant hardware, they are highly vulnerable to such as node compromising attacks. thus making it necessary to ascertain data trustworthiness and reputation of sensor nodes is crucial for WSN. Iterative filtering algorithms were found out to be very helpful in this purposes. such algorithms provides the aggregate the data from multiple data from multiple sources and also provide the trust assessements of these sources, usually in a form corresponding weight factors assigned to data provided each source .in this paper demonstrates the several existing iterative filtering algorithms, while significantly more robust against the collusion attacks than the simple averaging method. these algorithm are susceptible to the most sophisticated collusion attack scenario presented in this paper. we propose an improvement for iterative filtering techniques by providing initial approximation for these algorithms which make them not only collusion robust, but also get more accurate and faster converging.