Application Taint Analysis

Application Taint Analysis is a dynamic program analysis technique that tracks the flow of sensitive data through a mobile application by marking (tainting) such data at its source and monitoring its propagation across execution paths to detect unauthorized information leaks or malicious behavior.

112

Publications

12.5K

Citations

364

Authors

140

Institutions

Publications per year

2017–2026

45

Variants

Taint Analysis

Authors

364

  1. EB
    Eric Bodden

    Technische Universität Darmstadt, Germany

    13 publications · 3.5K citations

    13

    h-index

  2. JK
    Jacques Klein

    University of Luxembourg, Luxembourg

    9 publications · 3.1K citations

    9

    h-index

  3. PM
    Patrick McDaniel

    Pennsylvania State University, United States

    8 publications · 6.6K citations

    8

    h-index

  4. SA
    Steven Arzt

    Technische Universität Darmstadt, Germany

    7 publications · 3.1K citations

    7

    h-index

  5. DO
    Damien Octeau

    Pennsylvania State University, United States

    7 publications · 3K citations

    7

    h-index

1–5 of 364

Venues

  1. ACM SIGPLAN Notices

    4 publications · 1K citations

    4

    h-index

  2. 3

    h-index

  3. IEEE Transactions on Software Engineering

    TSE · 3 publications · 82 citations

    3

    h-index

  4. TUbilio (Technical University of Darmstadt)

    Repository · 2 publications · 143 citations

    2

    h-index

  5. Empirical Software Engineering

    2 publications · 65 citations

    2

    h-index

1–5