Graph-based Attribution

Graph-Based Attribution is a methodological framework within malware attribution that leverages graph theory to model and analyze relationships among cyber entities, distinguishing itself by representing malicious activities, infrastructure, and actors as nodes and edges to infer attribution through structural and behavioral patterns in the graph.

8

Publications

158

Citations

35

Authors

15

Institutions

Publications per year

2017–2026

6

Authors

35

  1. XW
    Xinchao Wang

    National University of Singapore, Singapore

    1 publications · 28 citations

    1

    h-index

  2. QX
    Qi Xiong

    City University of Hong Kong, Hong Kong SAR China

    1 publications · 17 citations

    1

    h-index

  3. HT
    Hanghang Tong

    University of Illinois Urbana-Champaign, United States

    1 publications · 15 citations

    1

    h-index

  4. SD
    Simon D. Duque Antón

    German Research Centre for Artificial Intelligence, Germany

    1 publications · 23 citations

    1

    h-index

  5. PF
    Peter F. Sweeney

    IBM (United States), United States

    1 publications · 19 citations

    1

    h-index

1–5 of 35

Venues

  1. International Journal on Cyber Situational Awareness

    IJCSA · 1 publications · 23 citations

    1

    h-index

  2. 1

    h-index

  3. Information Sciences

    1 publications · 24 citations

    1

    h-index

  4. IEEE Open Journal of the Communications Society

    IOJCAZ · 1 publications · 10 citations

1–4