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Robust machine learning algorithms in embedded devices to obtain novel insights and enable real-time decision making while ensuring system security and the privacy of users.

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Competitive advantage

  • Fundamental and multidisciplinary expertise in real-time embedded analytics for Internet of Things (IoT) and networked systems that can provide:
  • Novel business, environmental and system insights through seamless non-invasive monitoring
  • Security of networked systems
  • Minimal privacy risk for users, and
  • Improvements in the overall performance and usability of networked systems
  • This technology has demonstrated widespread application in:
  • Detection of malicious mobile apps
  • Real-time continuous identification of individuals and machines
  • Energy efficient sensing of user activities
  • Detection of anomalous operation of networks and devices
  • Voice biometric systems and countermeasures to spoofing attacks

Impact

  • Better security and improved usability of networked systems

Successful applications

  • Automatic inference of user emotion and mental state
  • Creation of a ‘breathprint’ for continuous user identification and authentication

Capabilities and facilities

  • State of the art laboratories equipped with a multitude of sensors, wearables, and state-of-the-art equipment for signal capture and analysis