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A Comparative Analysis of Threat Modelling Methods: STRIDE, DREAD, VAST, PASTA, OCTAVE, and LINDDUN

  • Nitin Naik*
  • , Paul Jenkins
  • , Paul Grace
  • , Dishita Naik
  • , S. Prajapat
  • , Jingping Song
  • *Awdur cyfatebol y gwaith hwn

Allbwn ymchwil: Pennod mewn Llyfr/Adroddiad/Trafodion CynhadleddCyfraniad mewn cynhadleddadolygiad gan gymheiriaid

12 Dyfyniadau (Scopus)

Crynodeb

Novel cybersecurity threats are constantly emerging and posing significant security challenges to organisations; therefore, it is important for organisations to proactively analyse the existing and emerging cybersecurity threats against their systems. Threat modelling methods are very effective in proactively analysing cybersecurity threats and enhancing organisational security policies and defence mechanisms against these cybersecurity threats. Several threat modelling methods have been proposed, and it is important for security experts to select the appropriate threat modelling methods for an organisation according to their specific security challenges and cybersecurity threats. This paper will present a comparative analysis of six threat modelling methods: STRIDE, DREAD, VAST, PASTA, OCTAVE, and LINDDUN. It will provide a concise description of all the aforementioned threat modelling methods, and subsequently, a comparative analysis of these six threat modelling methods for highlighting their relative strengths and limitations.

Iaith wreiddiolSaesneg
TeitlContributions Presented at The International Conference on Computing, Communication, Cybersecurity and AI - The C3AI 2024
GolygyddionNitin Naik, Paul Grace, Paul Jenkins, Shaligram Prajapat
CyhoeddwrSpringer Science and Business Media Deutschland GmbH
Tudalennau271-280
Nifer y tudalennau10
ISBN (Argraffiad)9783031744426
Dynodwyr Gwrthrych Digidol (DOIs)
StatwsCyhoeddwyd - 20 Rhag 2024
DigwyddiadInternational Conference on Computing, Communication, Cybersecurity and AI, C3AI 2024 - London, Y Deyrnas Unedig
Hyd: 3 Gorff 20244 Gorff 2024

Cyfres gyhoeddiadau

EnwLecture Notes in Networks and Systems
Cyfrol884 LNNS
ISSN (Argraffiad)2367-3370
ISSN (Electronig)2367-3389

Cynhadledd

CynhadleddInternational Conference on Computing, Communication, Cybersecurity and AI, C3AI 2024
Gwlad/TiriogaethY Deyrnas Unedig
DinasLondon
Cyfnod3/07/244/07/24

Dyfynnu hyn