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Ph.D. candidate in Cybersecurity for Signal Processing and Data Fusion

Ph.D. candidate in Cybersecurity for Signal Processing and Data Fusion
Job Advertisement:

Ph.D. candidate in Cybersecurity for Signal Processing and Data Fusion

Links:
Job:

Research Assistant

Contact Person:

Benjamin Noack or Uwe D. Hanebeck

Job Description

Cybersecurity for Signal Processing and Data Fusion

Modern applications in Industry 4.0 and the Internet of Things rely on sensor data collected in distributed networks. Privacy is and will be a major concern in ubiquitous, distributed sensor systems. However, processing sensor data and preserving privacy are difficult to achieve at the same time. Addressing the combination of these tasks will be the key for future applications, e.g., to enable in-network processing of sensor data or cloud-based machine learning with protected data.

 

Be the Future Engineer of Secure Sensor Platforms

We need to address multiple research questions to connect sensors to the cloud:

  • How can we protect the privacy of the data owners?
  • How can we implement signal processing on protected data?
  • How can we provide secure environments resilient to cyber threats?

 

Job Offer

We are looking for a Ph.D. candidate who investigates privacy-preserving multisensor data processing!

This position is part of our joint research project SeReMo (Secure Remote Monitoring) in close collaboration with SEKAS GmbH  and the research group Cryptography and IT Security.

 

Key Tasks:

  • Investigation and application of cryptographic methods for secure sensor data processing,
  • Investigation of order-preserving encryption for privacy-preserving comparisons of sensor data and verification of warning thresholds,
  • Development of methods for privacy-preserving signal processing and state estimation,
  • Prototypical implementation of the investigated methods for secure processing in the cloud

 

Further information:

Contact: Benjamin Noack
Job Advertisement: PDF (German)