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Dimensional analysis simplifies complex physical problems and guides experimental investigations, but it does not provide complete solutions. It identifies the dimensionless groups that influence a phenomenon, but experimental data is needed to establish the specific relationships and validate theoretical predictions.
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IR spectra are divided into two main regions: the diagnostic region and the fingerprint region. The diagnostic region of the spectrum lies above 1500 cm−1. The absorptions resulting from single-bond vibrations of the N–H, C–H, and O–H stretch at higher wavenumbers and appear on the left side of the spectrum. The stretching absorptions of the C≡C and C≡N occur between 2100–2300 cm−1. In contrast, those arising from stretching absorptions of the...
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Esquema de Huella Dactilar Probabilística para Datos Correlacionados

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
Resumen
Este resumen es generado por máquina.

Este estudio presenta un nuevo esquema de huella dactilar probabilística para rastrear fugas de datos de proveedores de servicios. Mejora la privacidad de los datos al tener en cuenta las correlaciones de datos y utilizar códigos de huella dactilar robustos.

Palabras clave:
Compartición de datosHuella dactilarResponsabilidad

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Área de la Ciencia:

  • Ciencias de la Computación
  • Seguridad de Datos
  • Criptografía

Sus antecedentes:

  • Los individuos comparten datos personales para obtener servicios, arriesgando la confidencialidad.
  • La distribución no autorizada de datos por parte de los proveedores de servicios requiere la identificación de la fuente.
  • Los esquemas de huella dactilar existentes son vulnerables a ataques basados en correlación.

Objetivo del estudio:

  • Proponer un esquema de huella dactilar probabilística robusto y eficiente para datos personales.
  • Abordar las vulnerabilidades en los esquemas existentes contra ataques de correlación de datos.
  • Garantizar la rendición de cuentas por el intercambio no autorizado de datos personales.

Principales métodos:

  • Desarrolló un esquema de huella dactilar probabilística que considera la utilidad de los datos y las correlaciones inherentes.
  • Integró códigos de huella dactilar Boneh-Shaw para una mayor robustez contra la colusión.
  • Implementó y evaluó el esquema en datos genómicos reales.

Principales resultados:

  • El esquema propuesto genera huellas dactilares de manera eficiente manteniendo una alta utilidad de los datos.
  • Demostró robustez contra la colusión utilizando códigos Boneh-Shaw.
  • Los resultados experimentales confirman la eficiencia y robustez del esquema en datos genómicos.

Conclusiones:

  • El esquema de huella dactilar probabilística rastrea eficazmente las fugas de datos de los proveedores de servicios.
  • El esquema proporciona una solución robusta para la rendición de cuentas del propietario de los datos.
  • Este enfoque mejora la seguridad de los datos personales en el contexto del intercambio de servicios.