How does reducing the dimension of feature vectors impact Biometric Systems that use Homomorphic Encryption? - Purim, Andreis G. M. (Anais do Simpósio Brasileiro de Cibersegurança (SBSeg); 2025: Anais do XXV Simpósio Brasileiro de CibersegurançaDO - 10.5753/sbseg.2025.11515, 2025)
Homomorphic Encryption enables biometric systems to perform matching directly on encrypted feature vectors, preserving user privacy throughout the process. However, the high computational cost of encrypted-domain operations, especially on high-dimensional inputs, remain a major barrier to real-world use. This study presents a concrete example of how reducing the dimensionality of biometric feature vectors affects both matching accuracy and runtime, and discusses how system designers could estimate the trade-off between time savings and accuracy loss when choosing a target dimension. The code is available on Github.