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A Comparative Evaluation of Anomaly Detectors under Portscan Attacks

  • Ayesha Binte Ashfaq
  • Maria Joseph Robert
  • Asma Mumtaz
  • Muhammad Qasim Ali
  • Ali Sajjad
  • Syed Ali Khayam
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5230)

Abstract

Since the seminal 1998/1999 DARPA evaluations of intrusion detection systems, network attacks have evolved considerably. In particular, after the CodeRed worm of 2001, the volume and sophistication of self-propagating malicious code threats have been increasing at an alarming rate. Many anomaly detectors have been proposed, especially in the past few years, to combat these new and emerging network attacks. At this time, it is important to evaluate existing anomaly detectors to determine and learn from their strengths and shortcomings. In this paper, we evaluate the performance of eight prominent network-based anomaly detectors under malicious portscan attacks. These ADSs are evaluated on four criteria: accuracy (ROC curves), scalability (with respect to varying normal and attack traffic rates, and deployment points), complexity (CPU and memory requirements during training and classification,) and detection delay. These criteria are evaluated using two independently collected datasets with complementary strengths. Our results show that a few of the anomaly detectors provide high accuracy on one of the two datasets, but are unable to scale their accuracy across the datasets. Based on our experiments, we identify promising guidelines to improve the accuracy and scalability of existing and future anomaly detectors.

Keywords

False Alarm Maximum Entropy False Alarm Rate Intrusion Detection Anomaly Detector 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Ayesha Binte Ashfaq
    • 1
  • Maria Joseph Robert
    • 1
  • Asma Mumtaz
    • 1
  • Muhammad Qasim Ali
    • 1
  • Ali Sajjad
    • 1
  • Syed Ali Khayam
    • 1
  1. 1.School of Electrical Engineering & Computer ScienceNational University of Sciences & Technology (NUST)RawalpindiPakistan

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