Abstract: In today’s data-driven world, recommendation systems personalize user experiences across industries but rely on sensitive data, raising privacy concerns. Fully homomorphic encryption (FHE) ...
Abstract: Existing research on privacy-preserving face recognition primarily focuses on securing biometric templates but performs distance similarity computations in plaintext, which exposes sensitive ...
Researchers from Boston University, Northeastern University, KAIST, and University of Murcia, et al. have released “FHECore: Rethinking GPU Microarchitecture for Fully Homomorphic Encryption”.
A sophisticated, cross-platform keylogger written in Python with advanced features including AES-256 encryption, silent background operation, automatic startup/restart capabilities, and daily log ...
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