Sensor-based Anomaly Detection

Sensor-Based Anomaly Detection is a systematic method for identifying deviations from normal operational behavior in critical infrastructure systems by analyzing real-time data streams collected through physical or virtual sensors.

491

Publications

22.7K

Citations

1.6K

Authors

630

Institutions

Publications per year

2017–2026

309

Authors

1.6K

  1. DL
    Datong Liu

    Harbin Institute of Technology, China

    8 publications · 268 citations

    8

    h-index

  2. CL
    Christopher Leckie

    The University of Melbourne, Australia

    6 publications · 575 citations

    6

    h-index

  3. OS
    Osman Salem

    Université Paris Cité, France

    6 publications · 359 citations

    6

    h-index

  4. GF
    Giuseppe Fabio Ceschini

    University of Ferrara, Italy

    6 publications · 82 citations

    6

    h-index

  5. SR
    Sutharshan Rajasegarar

    The University of Melbourne, Australia

    6 publications · 575 citations

    6

    h-index

1–5 of 1.6K

Venues

  1. Sensors

    28 publications · 1.3K citations

    21

    h-index

  2. IEEE Access

    16 publications · 865 citations

    15

    h-index

  3. IEEE Internet of Things Journal

    13 publications · 915 citations

    13

    h-index

  4. 9

    h-index

  5. IEEE Sensors Journal

    7 publications · 388 citations

    8

    h-index

1–5