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Of daemons and men: reducing false positive rate in intrusion detection systems with file system footprint analysis

  • George MamalakisEmail author
  • Christos Diou
  • Andreas L. Symeonidis
  • Leonidas Georgiadis
Original Article

Abstract

In this work, we propose a methodology for reducing false alarms in file system intrusion detection systems, by taking into account the daemon’s file system footprint. More specifically, we experimentally show that sequences of outliers can serve as a distinguishing characteristic between true and false positives, and we show how analysing sequences of outliers can lead to lower false positive rates, while maintaining high detection rates. Based on this analysis, we developed an anomaly detection filter that learns outlier sequences using k-nearest neighbours with normalised longest common subsequence. Outlier sequences are then used as a filter to reduce false positives on the \(FI^2DS\) file system intrusion detection system. This filter is evaluated on both overlapping and non-overlapping sequences of outliers. In both cases, experiments performed on three real-world web servers and a honeynet show that our approach achieves significant false positive reduction rates (up to 50 times), without any degradation of the corresponding true positive detection rates.

Keywords

Intrusion detection systems Anomaly detection Sequences of outliers 

Notes

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

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Copyright information

© The Natural Computing Applications Forum 2018

Authors and Affiliations

  1. 1.Department of Electrical and Computer EngineeringAristotle University of ThessalonikiThessalonikiGreece

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