The existing resilient data aggregation algorithm doesn’t accurately judge under-attack level of each node in wireless sensor networks（ WSNs）

resulting in a low precision

propose a distributed resilient data aggregation algorithm based on Chi-square goodness of fitting. The algorithm firstly construct weights of trust of each node

calculates current estimation value of data sample of each cluster by exploiting time correlation of a sensor node at different time

to evaluate attack level using Chi-square goodness of fitting. Finally

through weighted arithmetic

increase precision of data recovery. In addition

Chi-square goodness of fitting can sense to slight data fluctuations

accurately thus the presented algorithm can better improve robust of network noise. Simulation result shows that data aggregation precision of the presented algorithm is greatly improved

which is better than existing data resilient aggregation algorithm.