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Real-Time Parameter Estimation for Modelling Malware Propagation on Business and Social Networks Within a Corporate Environment

EasyChair Preprint no. 3282, version 2

Versions: 12history
13 pagesDate: July 9, 2020

Abstract

Tackling malware that spreads through business and social networks is a big cybersecurity challenge for large organisations and enterprises. To address this problem, we propose a new real-time parameter estimation method for forecasting Trojan malware propagation in such an environment. We set up a novel framework to estimate the per-interaction transmission rate p and verify the results of the estimation through a combination of real and simulated data sets. We discuss the benefits of integrating interactions into malware propagation models and study the accuracy and performance of our estimator for the parameter p. We examine how this method enables us to incorporate early detection data into real-time forecasts and how we are thus able to model malware not yet seen before.

Keyphrases: agent-based model, compartmental model, Forecasting, Malware Propagation Model, networks, parameter estimation, real-time, simulations, spreading agent, stochastic modelling, Trojan malware, zeroday attack

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@Booklet{EasyChair:3282,
  author = {Stephanie Kiss and Xiao-Si Wang and Jessica Welding},
  title = {Real-Time Parameter Estimation for Modelling Malware Propagation on Business and Social Networks Within a Corporate Environment},
  howpublished = {EasyChair Preprint no. 3282},

  year = {EasyChair, 2020}}
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