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Related Experiment Videos

An integrated pattern recognition approach for intrusion detection.

Amod Pandit1, R Joe Stanley, Bruce McMillin

  • 1Department of Electrical and Computer Engineering, 127 Emerson Electric Co. Hall, University of Missouri-Rolla, Rolla, MO 65409, USA.

Biomedical Sciences Instrumentation
|June 28, 2002
PubMed
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This study introduces an automated intrusion detection system (IDS) to identify insider threats by analyzing system log files. The novel approach uses dynamic programming and ART1 clustering for anomaly detection in distributed systems.

Area of Science:

  • Computer Science
  • Cybersecurity
  • Artificial Intelligence

Background:

  • Computer systems face insider threats and external attacks.
  • Intrusion detection systems (IDS) are crucial for monitoring network data.
  • Automated tools are needed to detect security policy violations efficiently.

Purpose of the Study:

  • To propose an automated IDS for detecting insider threats in distributed systems.
  • To develop an anomaly detection model based on log file analysis.
  • To enhance security policy enforcement through automated violation detection.

Main Methods:

  • Integration of dynamic programming and Adaptive Resonance Theory (ART1) clustering.
  • Analysis of system log files to identify anomalous user behavior.

Related Experiment Videos

  • Alignment of log event sequences with prototypical task sequences for classification.

    • Main Results:

    • The proposed IDS effectively functions as an anomaly detector for insider threats.
    • The integrated approach successfully classifies aligned log event sequences for intrusion detection.
    • Demonstrated the model's efficacy on a Boots System prototype.

    Conclusions:

    • The developed automated IDS offers a robust solution for insider threat detection in distributed environments.
    • The combination of dynamic programming and ART1 clustering provides an effective method for log-based anomaly detection.
    • The research highlights the potential of automated systems in strengthening cybersecurity.