An Improved Method for Electromagnetic Streaming Data Anomaly Detection
Abstract— The electromagnetic data is a kind of real-time, streaming data, the usage of wireless devices can alter the energy value at the corresponding frequency point. To detect the usage of wireless devices timely, an improved CUSUM method(H-CUSUM) is proposed, which combined a nonparametric CUSUM algorithm with an adaptive sliding window and tolerance factor. Four experimental data sets are collected to evaluate the proposed method, The result shows that the proposed method can detect the change in electromagnetic streaming data with high coverage and low latency.
Index Terms— Change Point, H-CUSUM, Sliding Window, Tolerance Factor
Degang Sun, Yulan Hu, Zhixin Shi, Guokun Xu
Institute of Information Engineering, Chinese Academy of Sciences, CHINA
Degang Sun, Yulan Hu
School of Cyber Security, University of Chinese Academy of Sciences, CHINA
Cite: Degang Sun, Yulan Hu, Zhixin Shi, Guokun Xu, "An Improved Method for Electromagnetic Streaming Data Anomaly Detection," Proceedings of 2019 the 9th International Workshop on Computer Science and Engineering, pp. 246-252, Hong Kong, 15-17 June, 2019.