Intelligent Security

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Development of intelligent methods—such as adversarial machine learning and cyber threat intelligence—for automatically detecting, responding to, and preventing advanced persistent threats.

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Competitive advantage

  • Development of Cyber threat intelligence models such as intrusion detection, privacy-preserving, and digital forensics-based statistics, machine and deep learning models
  • Development of automated penetration testing methods based on AI planning
  • Design of new testbed architectures for Industry 4.0 networks
  • Leading analysis of how AI could develop automated cyber applications, for the Australian Army, Australian Federal Police (AFP), and the Cyber Security Cooperative Research Centre (CSCRC)
  • Advanced threat intelligence models for deterring cyber threats and reducing financial losses and critic infrastructure damages

Impact

  • The increase in everything-connected, online systems that both sense from and interact with the physical world poses a security risk. The extent to which countries such as Australia are already dependent on cyber-physical systems – which is projected to increase – means that the impact of any disruption is potentially catastrophic.

Successful applications

  • Evaluating Network Intrusion Detection based Deep Learning and Graph Models
  • A Collaborative Host-Network Anomaly Detection Framework for Internet of Things
  • A new intelligent wargaming web service-based Machine Learning for the Australian Army to understand human influences and behaviours

Capabilities and facilities

  • Cyber Range Labs
  • Digital Forensics Lab
  • IoT Lab