Research on Tolerant Aggression Algorithms for Data Aggregation in Wireless Sensor Networks

Abstract

In view of the security issues in the data aggregation process of wireless sensor networks, this paper uses an auto regressive moving average model to characterize the spatio-temporal characteristics of the collected data, and combines the wavelet transform to improve the data prediction model to effectively identify malicious injection attacks in the process of data aggregation. And trusted prediction results replace wrong data. In this paper, a simulation platform based on MATLAB is used to evaluate the complexity and effectiveness of the algorithm. The simulation results show that the proposed scheme improves the relevant indicators for detecting malicious attacks in the wireless sensor network and corrects the wrong aggregated data in time.