Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 40, 2023 No. 10
2933-2938

Time series anomaly detection for cyber physical systems based on adaptive interactive learning

Wu Guanchao
Ling Jie
School of Computer Science & Technology, Guangdong University of Technology, Guangzhou 510006, China
DOI: 10.19734/j.issn.1001-3695.2023.03.0095

Abstract

Detection against time series of cyber physical systems(CPS) is an important means of anomaly detection. How-ever, some existing time series anomaly detection methods often ignore the dependencies within the time series, making the predicted or reconstructed data establish poor dependencies, which in turn affects the anomaly detection performance. To address the above problems, this paper proposed a time series anomaly detection method for cyber physical systems via adaptive interactive learning and unscented Kalman filter. The method used neural networks to identify the hidden states of CPS, and then preserved the dependencies of the time series through global adaptive fusion and interactive learning. Moreover, the me-thod used the traceless Kalman filter to track the trend of the time series to enhance the robustness of the prediction process. Finally, the method evaluated anomalies by calculating anomaly scores. The average performance obtained by applying this method on three CPS datasets is 0.940 for F1 score, 0.965 for precision, and 91.7% for recall. The experimental results show that compared with other research methods in recent years, the proposed method can better preserve the time series dependencies, extract more accurate time series features, and thus improve the prediction performance of the model, resulting in better recall and F1 scores of anomaly detection, which has good application prospects.

Foundation Support

广东省重点领域研发计划资助项目(2019B010139002)
广州市重点领域研发计划资助项目(202007010004)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.03.0095
Publish at: Application Research of Computers Printed Article, Vol. 40, 2023 No. 10
Section: Algorithm Research & Explore
Pages: 2933-2938
Serial Number: 1001-3695(2023)10-008-2933-06

Publish History

[2023-05-19] Accepted Paper
[2023-10-05] Printed Article

Cite This Article

伍冠潮, 凌捷. 基于自适应交互学习的CPS时间序列异常检测 [J]. 计算机应用研究, 2023, 40 (10): 2933-2938. (Wu Guanchao, Ling Jie. Time series anomaly detection for cyber physical systems based on adaptive interactive learning [J]. Application Research of Computers, 2023, 40 (10): 2933-2938. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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