kth.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Mapping Cyber Threat Intelligence to Probabilistic Attack Graphs
Foreseeti AB, Stockholm, Sweden..
KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.ORCID iD: 0000-0003-3922-9606
KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.ORCID iD: 0000-0001-9886-6651
Foreseeti AB, Stockholm, Sweden..
2021 (English)In: PROCEEDINGS OF THE 2021 IEEE INTERNATIONAL CONFERENCE ON CYBER SECURITY AND RESILIENCE (IEEE CSR), Institute of Electrical and Electronics Engineers (IEEE) , 2021, p. 304-311Conference paper, Published paper (Refereed)
Abstract [en]

As cyber threats continue to grow and expertise resources are limited, organisations need to find ways to evaluate their resilience efficiently and take proactive measures against an attack from a specific adversary before it occurs. Threat modelling is an excellent method of assessing the resilience of ICT systems, forming Attack (Defense) Graphs (ADGs) that illustrate an adversary's attack vectors. Cyber Threat Intelligence (CTI) is information that helps understand the current cyber threats, but has little integration with ADGs. This paper contributes with an approach that resolves this problem by using CTI feeds of known threat actors to enrich ADGs under multiple reuse. This enables security analysts to take proactive measures and strengthen their ICT systems against current methods used by any threat actor that is believed to pose a threat to them.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2021. p. 304-311
National Category
Computer Systems Computer Sciences
Identifiers
URN: urn:nbn:se:kth:diva-304556DOI: 10.1109/CSR51186.2021.9527970ISI: 000705054100047Scopus ID: 2-s2.0-85115727510OAI: oai:DiVA.org:kth-304556DiVA, id: diva2:1609419
Conference
IEEE International Conference on Cyber Security and Resilience (IEEE CSR), JUL 26-28, 2021, ELECTR NETWORK
Note

Part of proceedings: ISBN 978-1-6654-0285-9, QC 20230117

Available from: 2021-11-08 Created: 2021-11-08 Last updated: 2023-01-17Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records

Ekstedt, MathiasAfzal, Zeeshan

Search in DiVA

By author/editor
Ekstedt, MathiasAfzal, Zeeshan
By organisation
Network and Systems Engineering
Computer SystemsComputer Sciences

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 103 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf