Vulnerability Pattern Mining

Vulnerability Pattern Mining is a systematic analytical approach within reverse engineering that identifies recurring structural or behavioral indicators of security weaknesses in software by distinguishing exploitable flaw signatures from benign code patterns through data-driven generalization.

5

Publications

131

Citations

20

Authors

11

Institutions

Publications per year

2017–2026

3

Authors

20

  1. CX
    Chaowei Xiao

    University of Michigan, United States

    1 publications · 17 citations

    1

    h-index

  2. ZL
    Zhechao Lin

    Jiangsu University, China

    1 publications · 11 citations

    1

    h-index

  3. AS
    Armin Sarabi

    University of Michigan, United States

    1 publications · 17 citations

    1

    h-index

  4. YN
    Yu Nong

    Washington State University, United States

    1 publications · 34 citations

    1

    h-index

  5. FC
    Feng Chen

    Virginia Tech, United States

    1 publications · 34 citations

    1

    h-index

1–5 of 20

Venues

  1. Software Quality Journal

    1 publications · 22 citations

    1

    h-index

  2. IEEE Transactions on Services Computing

    1 publications · 47 citations

    1

    h-index

  3. IEEE Internet of Things Journal

    1 publications · 16 citations

  4. Simulation Modelling Practice and Theory

    1 publications · 11 citations

1–4