Concepedia

Abuse Detection In Coding

Abuse Detection in Coding is a computational framework designed to identify and flag malicious, exploitative, or unintended uses of software code within programming environments by analyzing syntactic, semantic, and behavioral patterns that deviate from legitimate coding practices.

1

Publications

22

Citations

5

Authors

2

Institutions

Publications per year

2017–2026

1

Parents

Publications

1

1–2 of 1

Authors

5

  1. SP
    Seonhye Park

    Dong-Eui University, South Korea

    1 publications · 22 citations

    1

    h-index

  2. HK
    Hyoungshick Kim

    Sungkyunkwan University, South Korea

    1 publications · 22 citations

    1

    h-index

  3. DK
    Doowon Kim

    University of Maryland, College Park, United States

    1 publications · 22 citations

    1

    h-index

  4. SO
    Sanghak Oh

    Sungkyunkwan University, South Korea

    1 publications · 22 citations

    1

    h-index

  5. KL
    Ki-Ho Lee

    Sungkyunkwan University, South Korea

    1 publications · 22 citations

    1

    h-index

1–5 of 5

Institutions

2

  1. Sungkyunkwan University

    Seoul, South Korea

    1 h-index

    4 publications

    88 citations

  2. University of Tennessee at Knoxville

    Knoxville, United States

    1 h-index

    1 publications

    22 citations

  3. Korea University

    Seoul, South Korea

    1 publications

    14 citations

1–3 of 2

Venues

  1. Annual Computer Security Applications Conference

    Conference · 1 publications · 14 citations

1–1