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Improving the Effectiveness of Cyberdefense Measures

In: Cyberdefense

Author

Listed:
  • Sébastien Gillard

    (Military Academy at the Swiss Federal Institute of Technology Zurich)

  • Cédric Aeschlimann

    (Military Academy at the Swiss Federal Institute of Technology Zurich)

Abstract

We present and illustrate a recursive model which automatically organizes relationships between indicators of compromise (IoC) into richer information sets. It combines insights from natural language processing, supervised clustering, and network analysis to identify relations between IoC and thus to reduce information fragmentation. The quality of this combined information improves with every IoC that is added to the network, so that defenders can generate a more comprehensive and complete picture about a threat almost in real time and at very low transaction cost.

Suggested Citation

  • Sébastien Gillard & Cédric Aeschlimann, 2023. "Improving the Effectiveness of Cyberdefense Measures," International Series in Operations Research & Management Science, in: Marcus Matthias Keupp (ed.), Cyberdefense, chapter 0, pages 205-219, Springer.
    • Handle: RePEc:spr:isochp:978-3-031-30191-9_14
    DOI: 10.1007/978-3-031-30191-9_14
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