Tainted Data Analysis

Tainted Data Analysis is a static vulnerability analysis method that identifies and tracks untrusted input data as it propagates through a program to detect potential security flaws arising from improper handling of such data.

20

Publications

846

Citations

54

Authors

27

Institutions

Publications per year

2017–2026

7

Variants

Taint Analysis

Authors

54

  1. ZL
    Zheng Li

    Florida International University, United States

    2 publications · 250 citations

    2

    h-index

  2. KP
    Kenneth Po

    University of Toronto, Canada

    2 publications · 250 citations

    2

    h-index

  3. AG
    Ashvin Goel

    University of Toronto, Canada

    2 publications · 250 citations

    2

    h-index

  4. SC
    Stephen Chong

    Harvard University Press, United States

    2 publications · 82 citations

    2

    h-index

  5. ED
    Eyal de Lara

    University of Toronto, Canada

    2 publications · 250 citations

    2

    h-index

1–5 of 54

Venues

  1. ACM SIGPLAN Notices

    1 publications · 23 citations

    1

    h-index

  2. Sensors and Actuators B Chemical

    1 publications · 103 citations

    1

    h-index

  3. Recent Advances in Intrusion Detection

    Conference · 1 publications · 18 citations

    1

    h-index

  4. DBMS archive

    1 publications · 37 citations

    1

    h-index

  5. Expert Systems with Applications

    1 publications · 66 citations

    1

    h-index

1–5