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Multimedia Technology and Enhanced Learning. 5th EAI International Conference, ICMTEL 2023, Leicester, UK, April 28-29, 2023, Proceedings, Part IV

Research Article

On the Trend and Problems of IoT Data Anomaly Detection

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BibTeX Plain Text
  • @INPROCEEDINGS{10.1007/978-3-031-50580-5_31,
        author={Shuai Li and Lejie Li and Kaining Xu and Jiafeng Yang and Siying Qu},
        title={On the Trend and Problems of IoT Data Anomaly Detection},
        proceedings={Multimedia Technology and Enhanced Learning. 5th EAI International Conference, ICMTEL 2023, Leicester, UK, April 28-29, 2023, Proceedings, Part IV},
        proceedings_a={ICMTEL PART 4},
        year={2024},
        month={2},
        keywords={Internet of Things Anomaly detection Trend},
        doi={10.1007/978-3-031-50580-5_31}
    }
    
  • Shuai Li
    Lejie Li
    Kaining Xu
    Jiafeng Yang
    Siying Qu
    Year: 2024
    On the Trend and Problems of IoT Data Anomaly Detection
    ICMTEL PART 4
    Springer
    DOI: 10.1007/978-3-031-50580-5_31
Shuai Li1, Lejie Li2,*, Kaining Xu2, Jiafeng Yang2, Siying Qu2
  • 1: School of EE, University of Jinan
  • 2: Jinan Lingsheng Info Tech. Co. Ltd., Huaiyin District
*Contact email: lejie.li@dmml.stream

Abstract

With the rapid development of Internet technology, the Internet of Things is also constantly developing and progressing. More and more areas are starting to see connected devices, and more and more data is being generated by them. Effective data analysis and detection can prevent network intrusions and predict future trends. In recent years, with the breakthrough of computer technology, machine learning has shown good results in anomaly detection. Therefore, the research on anomaly detection of Internet of Things data has gradually increased and deepened. This work analyzes and summarizes the research trends in this field. First, we use keyword search to export articles in this field. Then we use the tool bibliometrix to generate statistical charts and trend charts for exported articles. At last, we analyze and summarize the generated two graphs. In the process of analysis, we have a detailed description of the phenomenon and a cause analysis. Finally, the future research direction in this field is derived.

Keywords
Internet of Things Anomaly detection Trend
Published
2024-02-21
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-031-50580-5_31
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