Statistical Analysis in Cyberspace: Data veracity, completeness, and clustering

Research output: ThesisDissertation (TU Delft)

103 Downloads (Pure)

Abstract

This thesis presents several methodological and statistical solutions to problems encountered in cyber security. We investigated the effects of compromised data veracity in state estimators and fraud detection systems, a model to impute missing data in attributes of linked observations, and an unsupervised approach to detect infected machines in a computer network.
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • Delft University of Technology
Supervisors/Advisors
  • Verwer, S.E., Supervisor
  • van den Berg, J., Supervisor
  • Lagendijk, R.L., Supervisor
Thesis sponsors
Award date7 Jun 2021
Place of PublicationGouda
Print ISBNs978-94-6423-299-8
DOIs
Publication statusPublished - 2021

Keywords

  • Cybersecurity
  • Unsupervised learning
  • Imputation
  • Data veracity

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