An Effective Resilient Data Aggregation Algorithm in Wireless Sensor Networks

Resilient aggregation is an effective method to deal with the malicious attack on input data of the aggregation function. However, the current resilient algorithm is always energy exhausting, and does not consider the aggregation function and the attack detection synthetically, which may affect the accuracy of aggregation result. A novel resilient data aggregation algorithm is proposed in this paper trying to solve this problem. Based on the prevalent clustering method, the algorithm firstly detects whether there is an attack in networks or not, and then computes the information utility measures from which we can evaluate the under-attack level of each cluster. Finally it uses these measures as parameters jointly to calculate the aggregation output. Compared with the existing techniques, the new algorithm is more resilient and can upgrade the accuracy and applicability of the aggregation function. Simulation results show the effectiveness of the presented algorithm.