Causal Modeling for Cybersecurity

EasyChair Preprint 628

Abstract

Causal modeling is very useful in the pursuit of cybersecurity since it often helps us to execute actions leading to fruitful results, without performing unnecessary computations that might affect the values of other variables. The causative factors that are necessary and sufficient, are explored, with the help of modeling a real-life example taken from 2017, United States cybersecurity case. One can recommend future company policies, based on the causal modeling results. It also makes us understand how an event such as a breach of cybersecurity occurs, and how it can be dealt with.

Keyphrases: causal modeling, data leakage, graph maneuvered according to causal modeling, preventing computational virus

@booklet{EasyChair:628,
  author    = {Suchitra Abel and Licheng Xiao and Hairong Wang},
  title     = {Causal Modeling for Cybersecurity},
  doi       = {10.29007/dm1f},
  howpublished = {EasyChair Preprint 628},
  year      = {EasyChair, 2018}}