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Seeded Ising Model and Distributed Biometric Template Storage and Matching.

Hyeong In Choi1,2, Sungjin Lee3, Hwan Pyo Moon4

  • 1Department of Mathematics, Seoul National University, Seoul 08826, Korea.

Entropy (Basel, Switzerland)
|August 6, 2021
PubMed
Summary

The Seeded Ising Model (SIM) can reconstruct full biometric templates from partial data, posing a security risk. This study analyzes SIM

Keywords:
Ising modelbiometric templatedistributed biometricspartial template

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Area of Science:

  • Biometrics
  • Cybersecurity
  • Statistical Modeling

Background:

  • The Seeded Ising Model (SIM) allows biometric template reconstruction from partial information.
  • This reconstruction capability presents a potential security threat to biometric identity management systems.
  • Intruder templates can be generated and potentially accepted as genuine.

Purpose of the Study:

  • To systematically analyze the security breach potential of the Seeded Ising Model in biometrics.
  • To evaluate the probability of accepting intruder templates as genuine.
  • To investigate optimal strategies for dividing templates and conducting secure, distributed matching.

Main Methods:

  • Analysis of the Seeded Ising Model for biometric template reconstruction.
  • Statistical experiments to assess intruder match rates under various scenarios.
  • Development of a distributed matching protocol using siloed partial templates.

Main Results:

  • Quantification of the security risks associated with SIM-based template reconstruction.
  • Identification of optimal methods for partitioning biometric templates into partial templates.
  • Validation of a secure matching process that avoids centralizing full templates.

Conclusions:

  • The Seeded Ising Model presents a significant security vulnerability in biometric systems.
  • A novel distributed matching approach mitigates risks by processing partial templates in silos.
  • This research provides insights into securing biometric data against reconstruction attacks.