EVA: An Event-Conditioned Framework for Privacy-Preserving Face Authentication Services

However, existing face anonymization methods mainly focus on imagelevel de-identification and do not fully support stable repeated authentication in a protected identity space. This paper presents EVA, an event-conditioned framework for privacy-preserving face authentication services.

EVA treats an event as a servicescoped diversification factor and combines it with a userheld key to bind face-derived representations to an eventspecific virtual identity. During enrollment and verification, EVA performs identity processing, biometric stabilization, event-key binding, and cancelable template generation, followed by cloudside virtual identity issuance and protected-domain matching. Preliminary experiments with off-the-shelf recognizers show that EVA suppresses original identity cues while maintaining withinevent consistency for repeated verification.