Suspicious Behavior Detection

Suspicious Behavior Detection is a computational framework within casino security systems that identifies anomalous or potentially fraudulent activities by analyzing behavioral patterns of individuals through surveillance data, distinguishing itself from general monitoring methods by its focus on predictive indicators of deviant conduct.

421

Publications

19K

Citations

1.3K

Authors

532

Institutions

Publications per year

2017–2026

202

Authors

1.3K

  1. CF
    Christos Faloutsos

    Carnegie Mellon University, United States

    10 publications · 1.1K citations

    10

    h-index

  2. AB
    Alex Beutel

    Google (United States), United States

    7 publications · 890 citations

    7

    h-index

  3. BH
    Bryan Hooi

    National University of Singapore, Singapore

    6 publications · 566 citations

    6

    h-index

  4. HK
    Huy Kang Kim

    Korea University, South Korea

    6 publications · 129 citations

    6

    h-index

  5. LS
    Li Sun

    Xi'an Jiaotong University, China

    4 publications · 231 citations

    4

    h-index

1–5 of 1.3K

Venues

  1. IEEE Access

    11 publications · 433 citations

    11

    h-index

  2. arXiv (Cornell University)

    Repository · 6 publications · 219 citations

    7

    h-index

  3. Expert Systems with Applications

    6 publications · 278 citations

    6

    h-index

  4. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 5 publications · 277 citations

    5

    h-index

  5. Security and Communication Networks

    5 publications · 91 citations

    5

    h-index

1–5