Contextual information fusion for intrusion detection: a survey and taxonomy

@article{AlEroud2017ContextualIF,
  title={Contextual information fusion for intrusion detection: a survey and taxonomy},
  author={Ahmed F. AlEroud and George Karabatis},
  journal={Knowledge and Information Systems},
  year={2017},
  volume={52},
  pages={563-619}
}
Research in cyber-security has demonstrated that dealing with cyber-attacks is by no means an easy task. One particular limitation of existing research originates from the uncertainty of information that is gathered to discover attacks. This uncertainty is partly due to the lack of attack prediction models that utilize contextual information to analyze activities that target computer networks. The focus of this paper is a comprehensive review of data analytics paradigms for intrusion detection… CONTINUE READING

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