skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Explore Research Products in the PAR
It may take a few hours for recently added research products to appear in PAR search results.


  • Home
  • Search Results
  • Page 1 of 2

Search for: All records

Creators/Authors contains: "Ayday, E"

Note: When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher. Some full text articles may not yet be available without a charge during the embargo (administrative interval).
What is a DOI Number?

Some links on this page may take you to non-federal websites. Their policies may differ from this site.

  1. ; ; ; ; (, Proceedings of 30th European Symposium on Research in Computer Security (ESORICS))
    Free, publicly-accessible full text available September 27, 2026
  2. ; ; (, Proceedings of the American Medical Informatics Association (AMIA) Annual Summit)
    Free, publicly-accessible full text available March 1, 2026
  3. ; ; ; ; ; ; (, Proceedings of AAAI Conference on Artificial Intelligence (AAAI-25))
    Free, publicly-accessible full text available February 25, 2026
  4. ; ; (, 24th Privacy Enhancing Technologies Symposium)
    Accepted Manuscript Full Text Available
  5. ; (, ACM)
    Accepted Manuscript Full Text Available
  6. ; ; (, Proceedings on Privacy Enhancing Technologies (PoPETs))
    Accepted Manuscript Full Text Available
  7. ; ; ; (, Proceedings of The Annual Network & Distributed System Security Symposium)
    Accepted Manuscript Full Text Available
  8. ; ; ; ; ; (, AMIA)
    Accepted Manuscript Full Text Available
  9. ; ; ; ; ; (, AMIA Jt Summits Transl Sci Proc 2023)
    Kinship relationship estimation plays a significant role in today's genome studies. Since genetic data are mostly stored and protected in different silos, retrieving the desirable kinship relationships across federated data warehouses is a non-trivial problem. The ability to identify and connect related individuals is important for both research and clinical applications. In this work, we propose a new privacy-preserving kinship relationship estimation framework: Incremental Update Kinship Identification (INK). The proposed framework includes three key components that allow us to control the balance between privacy and accuracy (of kinship estimation): an incremental process coupled with the use of auxiliary information and informative scores. Our empirical evaluation shows that INK can achieve higher kinship identification correctness while exposing fewer genetic markers. 
    more » « less
    Accepted Manuscript Full Text Available
  10. ; ; ; ; ; (, American Medical Informatics Association (AMIA) Annual Symposium)
    Accepted Manuscript Full Text Available