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BlowLive: Blow-Based Multi-Factor Biometrics with Liveness Detection and Revocability

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arXiv:2606. 25998v1 Announce Type: new Abstract: Biometric authentication systems are increasingly deployed in security-critical applications, yet existing physiological and behavioral biometrics suffer from fundamental limitations: 1) they are vulnerable to spoofing attacks due to unreliable liveness detection, 2) biometric templates may leak privacy-sensitive information 3) intra-user variability results in accuracy degradation, and 4) it is difficult to revoke physiological biometrics and safeguard them over long-term use.

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Authors: Eyasu Getahun Chekole, Howard Halim, Dani\"el Reijsbergen, Jianying Zhou
Released: 2026-06-25 (14d ago)
Topic: Related to current project
Relation to my work: Read next because BlowLive: Blow-Based Multi-Factor Biometrics with Liveness Detection and Revocability overlaps with clean result "LoRA persona trained on <A> alone emits <B> at 23.5% when a co-trained partner learns <A>...<B>, vs 0% control on Qwen2.5-7B-Instruct (MODERATE confidence)", clean result "Leakage rate is a usable signal for recovering trigger-shaped phrases on Gaperon-1125-1B without knowing the hidden trigger itself (MODERATE confidence)", clean result "Language-mismatch LoRA SFT on Qwen2.5-7B leaks the trained completion language into bystander directives the model was never trained on, absent under same-language SFT (LOW confidence)". Matching terms: strong, eval, rate, implement, extraction, factor. Source: arxiv cs.CR (Cryptography and Security).
arXiv: 2606.25998

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