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Towards a Machine Learning Based Situational Awareness Framework for Cybersecurity: An SDN Implementation.

Yannis Nikoloudakis1,2, Ioannis Kefaloukos2, Stylianos Klados2

  • 1Department of Information & Communications Systems Engineering, University of the Aegean, Neo Karlovasi, 83200 Samos, Greece.

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PubMed
Summary
This summary is machine-generated.

This study introduces a machine learning framework for enhanced cybersecurity situational awareness. It improves threat detection and network security by assessing devices against vulnerabilities and using an improved Intrusion Detection System (IDS).

Keywords:
SDNintrusion detection systemsmachine learningsituational awarenesssoftware defined networkingvulnerability assessment

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Area of Science:

  • Computer Science
  • Cybersecurity
  • Network Security

Background:

  • The expanding cyber-threat landscape poses significant risks to internet-connected infrastructures.
  • Increasingly sophisticated cyber-attacks necessitate advanced defense mechanisms.

Purpose of the Study:

  • To develop a machine learning-based situational awareness framework for enhanced network security.
  • To improve the detection of network-enabled entities and assess their vulnerabilities in real-time.

Main Methods:

  • Utilizing Software-Defined Networking (SDN) for real-time network awareness.
  • Implementing a machine learning-based Intrusion Detection System (IDS) trained on heterogeneous data, including Common Vulnerability Enumeration (CVE) IDs.
  • Assessing network entities against known vulnerabilities and assigning them to appropriate network slices.

Main Results:

  • The proposed framework demonstrated improved prediction accuracy for threat detection.
  • A neural network trained with operational environment data achieved higher accuracy than conventional models.
  • Real-life evaluation showed an increase of over 4% in overall prediction accuracy.

Conclusions:

  • Machine learning, particularly neural networks trained on heterogeneous data, significantly enhances cybersecurity situational awareness.
  • The framework effectively addresses system vulnerabilities and mitigates the impact of cyber threats.
  • The integration of SDN and ML-based IDS offers a robust solution for modern network security challenges.