Secure data aggregation in WSN using iterative filtering algorithm

In WSN Aggregation is considered as the most susceptible to node compromising attacks, as wireless sensor networks are not more secured so they are more vulnerable to this type of attacks. For WSN it is essential to check the trustworthiness of the data & reputation of sensor nodes. To handle this issue Iterative Filtering acts as a best option. In Iterative filtering algorithm (IF) the data is aggregated concurrently from multiple sources & IF also render trust assessment of these sources. The trust assessment is in the form of similar weight factors assigned to data supplied by each source. Considering the security as major issue in WSN, In this paper we proposed an advancement for IF method by providing approximation which will make them collusion robust and is converging fast. Advancement in the Iterative Filtering algorithm will enhance the performance of the system with good potential for implementation in WSN, IF algorithm is stretched with novel method for collusion detection & revocation based on an initial approximation of the aggregate values as well as distribution of differences of each sensor readings. The proposed system performance is checked through extensive simulation in C#. The simulation demonstrates the improved results. The RMS value in the graphs for series 2(0.1, 0.18, 0.22, 0.22, 0.22, 0.3, 0.36, 0.38) with standard deviation ranging from 0.5 to 4 shows that the proposed system performance is better as compare to existing system.