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Probabilistic Fingerprinting Scheme for Correlated Data.

Emre Yilmaz1, Erman Ayday2

  • 1University of Houston-Downtown, Houston, TX 77002, USA.

Data and Applications Security and Privacy XXXVII : 37Th Annual IFIP WG 11.3 Conference, Dbsec 2023, Sophia-Antipolis, France, July 19-21, 2023, Proceedings. Annual IFIP WG 11.3 Working Conference on Data and Applications Security (37Th
|December 22, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces a new probabilistic fingerprinting scheme to trace data leaks from service providers. It enhances data privacy by accounting for data correlations and using robust fingerprinting codes.

Keywords:
Data sharingFingerprintingLiability

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Area of Science:

  • Computer Science
  • Data Security
  • Cryptography

Background:

  • Individuals share personal data for services, risking confidentiality.
  • Unauthorized data distribution by service providers necessitates source identification.
  • Existing fingerprinting schemes are vulnerable to correlation-based attacks.

Purpose of the Study:

  • To propose a robust and efficient probabilistic fingerprinting scheme for personal data.
  • To address vulnerabilities in existing schemes against data correlation attacks.
  • To ensure accountability for unauthorized personal data sharing.

Main Methods:

  • Developed a probabilistic fingerprinting scheme considering data utility and inherent correlations.
  • Integrated Boneh-Shaw fingerprinting codes for enhanced robustness against collusion.
  • Implemented and evaluated the scheme on real genomic data.

Main Results:

  • The proposed scheme efficiently generates fingerprints while maintaining high data utility.
  • Demonstrated robustness against collusion using Boneh-Shaw codes.
  • Experimental results confirm the scheme's efficiency and robustness on genomic data.

Conclusions:

  • The probabilistic fingerprinting scheme effectively traces data leaks from service providers.
  • The scheme provides a robust solution for data owner accountability.
  • This approach enhances personal data security in the context of service sharing.