Dynamic Information Flow Tracking

Dynamic Information Flow Tracking is a dynamic analysis technique that monitors and records the propagation of data through a system during execution to identify how and where sensitive information influences program behavior, distinguishing it from static or hybrid approaches by its reliance on runtime observation.

58

Publications

6.4K

Citations

170

Authors

54

Institutions

Publications per year

2017–2026

16

Authors

170

  1. MD
    Michael Dalton

    NOAA National Marine Fisheries Service Alaska Fisheries Science Center, United States

    7 publications · 620 citations

    7

    h-index

  2. CK
    Christos Kozyrakis

    Stanford University, United States

    7 publications · 620 citations

    7

    h-index

  3. HK
    Hari Kannan

    Stanford University, United States

    6 publications · 546 citations

    6

    h-index

  4. JW
    Jae Wook Lee

    Korea Advanced Institute of Science and Technology, South Korea

    5 publications · 936 citations

    5

    h-index

  5. GE
    G. Edward Suh

    Cornell University, United States

    5 publications · 976 citations

    5

    h-index

1–5 of 170

Venues

  1. ACM SIGPLAN Notices

    3 publications · 152 citations

    3

    h-index

  2. ACM SIGARCH Computer Architecture News

    3 publications · 131 citations

    3

    h-index

  3. USENIX Security Symposium

    Conference · 2 publications · 71 citations

    2

    h-index

  4. ACM SIGOPS Operating Systems Review

    2 publications · 48 citations

    2

    h-index

  5. Proceedings of the ACM on Programming Languages

    PACMPL · 2 publications · 40 citations

    2

    h-index

1–5