Link anomaly detection algorithm for wireless sensor networks based on convolutional neural networks

To accurately detect abnormal links in wireless sensor networks，a CNN based wireless sensor network link anomaly detection algorithm is proposed. Design network link anomaly detection function using concurrent multithreading technology，and establish a training model for network link anomaly detection using CNN. Input network link data，convolve network link information，extract network link feature vectors，and analyze network link abnormal behavior through down sampling function processing. Use vector mapping to represent the abnormal part vector，and complete classification detection through Softmax function classifier. The experimental results show that the proposed method can effectively improve the accuracy of link anomaly classification and detection，and it takes a short time. © 2024 Editorial Board of Jilin University. All rights reserved.