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Related Experiment Videos

Governing Privacy-Preserving Face Recognition in Transport Infrastructures: A Comprehensive Review.

Eva María Benito Sanz1, Alba Gonzalo Primo1, Gaurav Choudhary1

  • 1Section of Cybersecurity Engineering, Department of Applied Mathematics and Computer Science, Technical University of Denmark (DTU), 2800 Kongens Lyngby, Denmark.

Sensors (Basel, Switzerland)
|May 13, 2026
PubMed
Summary

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Association Areas of the Cortex01:21

Association Areas of the Cortex

Association areas are regions of the cerebral cortex that do not have a specific sensory or motor function. Instead, they integrate and interpret information from various sources to enable higher cognitive processes such as memory, learning, and decision-making. Some key association areas include the following:
Prefrontal Association Area: This area is located in the frontal lobe and is involved in planning, decision-making, and moderating social behavior. It connects with primary motor areas,...

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Privacy-preserving face recognition in transport infrastructure faces challenges. While techniques exist to protect data, they are not widely used, highlighting a gap between research and practical, regulated implementation.

Area of Science:

  • Computer Science
  • Information Security
  • Transportation Engineering

Background:

  • Face recognition technology is increasingly used in transportation for efficiency and security.
  • This widespread deployment raises significant privacy and data protection concerns.
  • Existing research explores privacy-preserving methods to mitigate these risks.

Purpose of the Study:

  • To review privacy-preserving face recognition techniques for transport infrastructures.
  • To analyze challenges and gaps in implementing these techniques in real-world settings.
  • To identify needs for integrated approaches balancing privacy, performance, and regulation.

Main Methods:

  • Systematic literature review.
  • Analysis across technical, operational, and governance perspectives.
Keywords:
airportsbiometricsface recognitionprivacy preservationpublic transport

Related Experiment Videos

  • Synthesis of research findings on privacy-preserving face recognition.

    • Main Results:

    • Advanced privacy techniques (encryption, federated learning, de-identification) exist but are rarely implemented.
    • Operational systems often prioritize performance and scalability over privacy.
    • Governance studies highlight rights and accountability but lack technical integration.

    Conclusions:

    • A fragmented landscape exists between privacy research and practical deployment in transport.
    • There is a significant gap between theoretical privacy solutions and operational realities.
    • Integrated approaches are needed to align privacy techniques with deployment constraints and regulations.