Yakupoğlu Karaağaç, Cavidan

Profile Picture
Profile URL
https://hdl.handle.net/20.500.12573/2849
Name Variants
Cavidan Yakupoğlu Karaağaç
Karaagac, Cavidan Yakupoglu
Job Title
Öğr. Gör.
Email Address
cavidan.yakupoglu@agu.edu.tr
Main Affiliation
02. 04. Bilgisayar Mühendisliği
Status
Current Staff
Website
ORCID ID
Scopus Author ID
Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID

Sustainable Development Goals

SDG data is not available
This researcher does not have a Scopus ID.
This researcher does not have a WoS ID.
Scholarly Output

1

Articles

1

Views / Downloads

2/0

Supervised MSc Theses

0

Supervised PhD Theses

0

WoS Citation Count

0

Scopus Citation Count

0

WoS h-index

0

Scopus h-index

0

Patents

0

Projects

0

WoS Citations per Publication

0.00

Scopus Citations per Publication

0.00

Open Access Source

0

Supervised Theses

0

JournalCount
Turkish Journal of Electrical Engineering and Computer Sciences1
Current Page: 1 / 1

Scopus Quartile Distribution

Competency Cloud

GCRIS Competency Cloud

Filters

20251
Reset filters

Settings

Scholarly Output Search Results

Now showing 1 - 1 of 1
  • Thumbnail Image
    Article
    Optimizing Parameters for Efficient Computation With Fully Homomorphic Encryption Schemes
    (Tubitak Scientific & Technological Research Council Turkey, 2025) Karaagac, Cavidan Yakupoglu; Rohloff, Kurt
    In this study, we aim to provide a parameter selection approach for the BFVrns scheme, one of the prominent fully homomorphic encryption (FHE) schemes. Selecting parameters for lattice-based FHE schemes poses a practical challenge for both experts and nonexperts. To solve this problem, we introduce a hybrid approach that combines theoretical approach with experimental analysis. First, we employ regression analysis to examine the impact of parameters on both performance and security. The varying behavior of FHE parameters in terms of performance, security, and ciphertext expansion factor (CEF) makes parameter selection more challenging. To address this issue, we employ a multi-objective optimization algorithm to determine the optimal parameter set for performance, CEF, and security simultaneously. As a result of this optimization, we obtain an improved parameter set that enhances performance at a given security level while ensuring correctness and resistance to lattice-based attacks, maintaining at least 128-bit security. Our results achieve an average similar to 5x reduction in CEF and generally better performance compared to the parameter sets in a previous BFVrns study. Our approach serves as a semi-automated parameter selection method for the PALISADE homomorphic encryption library, a widely recognized FHE library. This study sets a precedent for other FHE libraries.