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Cyberattack Analysis Utilising Attack Tree with Weighted Mean Probability and Risk of Attack

  • Nitin Naik,
  • Paul Jenkins,
  • Paul Grace,
  • Shaligram Prajapat,
  • Dishita Naik,
  • Jingping Song,
  • Jian Xu,
  • Ricardo M. Czekster

摘要

As technology advances and AI becomes embedded and accepted into everyday life, the risk of cyberattacks by adversaries increases. These cyberattacks are ubiquitous affecting both businesses and individuals alike, and causing financial and reputational loss as a result. Numerous cyberattack analysis methods are available to analyse the risk of cyberattacks and offer the appropriate mitigation strategy. Nonetheless, several cyberattack analysis methods may not be effective and applicable in all cyberattack conditions due to several reasons such as their cost, complexity, resources and expertise. Therefore, this paper builds on an economical, simple and adaptable method for cyberattack analysis using an attack tree with weighted mean probability and risk of attack. It begins with an examination of a weighted mean approach followed by an investigation of the different types of weighted mean functions. Utilizing a series of orderly steps to perform a cyberattack analysis and assess its potential risk in an easy and effective manner. This method provides the means to calculate the potential risk of attack and therefore any mitigation that can be employed to minimise its effect.