BioTone
Multi-Signal Biometric Identity
Five biometrics. One smartphone. Zero specialized hardware.
The Problem
Credentials are the #1 attack vector
Phished Password
→
Stolen Token
→
Lateral Movement
→
Breach
Breaches from credentials
80%+
NSA User Pillar report
Hardware biometrics
$$$
Cost-prohibitive at scale
Single-factor biometric
1 Point
of failure to defeat
The Solution
Turn any smartphone into a biometric identity device
🔐
6 Independent Signals, 2 Auth Factors
Iris, palm, ear, voice, PPG pulse, and selfie liveness — six signals spanning something you are and point in time. Device attestation and geofencing extend to 4 factors.
📱
Standard Smartphone
No IR scanners, no vein sensors, no fingerprint readers. Uses the cameras and microphone already in every modern phone.
🧮
Multiplicative Security
Compromise one signal, learn nothing about the others. An attacker must defeat 3+ unrelated modalities simultaneously.
🔗
Layers On Top
Auth broker pattern — no rip-and-replace. Compatible with existing SSO, ICAM, CAC/PIV, and zero trust frameworks.
Biometric Signals
Six signals, independent sensors, zero correlation
👁️
Iris
Front camera
30% weight
🖐️
Palm
Rear camera
30% weight
🗣️
Voice
Microphone
25% weight
👂
Ear
Front camera
15% weight
💓
PPG Pulse
Rear camera
Liveness gate
All processing on-device. Raw biometric data never leaves the phone.
In the app
Iris
Phase-structure encoding from visible-light capture.
Placeholder UI — drop in a real app screenshot at signals/iris.png before presenting.
In the app
Palm
Texture and line structure from contactless palm imaging.
Placeholder UI — replace with signals/palm.png when ready.
In the app
Voice
Speaker embedding with time-bound digit challenge.
Placeholder UI — replace with signals/voice.png when ready.
In the app
Ear
Cartilage geometry from profile capture.
Placeholder UI — replace with signals/ear.png when ready.
In the app
Vitals (PPG)
Pulse-based liveness via camera; vetoes non-living presentation.
Placeholder UI — replace with signals/vitals.png when ready.
In the app
Presentation
Active liveness challenges (e.g., blink, motion) per session.
Placeholder UI — replace with signals/presentation.png when ready.
Anti-Spoofing
Three independent liveness gates
😑 → 😃
Selfie Liveness
Random blink + head turn challenges. Must respond in real time within a timeout window.
Defeats: photos, masks, screen replays
💓
PPG Pulse Gate
Detects cardiac blood pulse through fingertip. Vetoes entire authentication if no live pulse.
Defeats: all non-living artifacts
🔢
Voice Challenge
Time-bounded rotating 6-digit code (30s window). User must speak the current code live.
Defeats: pre-recorded audio replay
All liveness gates must pass. A perfect biometric match is rejected if liveness fails.
Security Posture
Multiplicative security from independent factors
Combined FAR
4×10⁻⁸
1 false accept per 25M attempts
Genuine Accept Rate
97.1%
Majority fusion (≥3 of 4)
False Rejection
2.9%
With retry policy
Liveness Pass Rate
~95%
Genuine users
Fusion requires weighted majority of factors to pass AND all liveness gates to pass.
Figures derived from internal benchmarking under controlled conditions with a limited test population. Combined FAR computed from per-factor independence assumptions. Not NIST Biometric Evaluation Program results. Independent validation scoped for pilot phase.
Competitive Positioning
Why multi-factor beats single-factor hardware
Dedicated hardware (Face ID, Palm Vein, NIR Iris)
Single Factor
✓ Lower per-factor EER (0.001-0.1%)
✗ One point of failure — defeat it, full access
✗ Requires $1,000+ specialized devices
✗ No server-side identity or enterprise control
✗ Platform-locked (iOS only for Face ID)
BioTone
6 Signals · 2 Auth Factors
✓ 4 identity signals (iris, palm, voice, ear) + PPG + selfie liveness
✓ Must defeat 3+ modalities simultaneously
✓ Any modern smartphone — $0 new hardware
✓ Server-side identity, full enterprise control
✓ iOS + Android, cross-platform
Security through factor independence, not hardware specialization.
Architecture
Zero-storage, three-part key disaggregation
BioTone never stores biometric templates or key material.
1
Customer Primary Server
On-premises or customer-controlled. Holds Key Part 1.
2
Customer Cloud
Azure, AWS, Oracle, or Google — customer's choice. Holds Key Part 2.
3
User's Device
Enrolled phone's secure enclave (Keychain/Keystore). Holds Key Part 3.
No single party — including BioTone — can reconstruct a template or authenticate on behalf of a user.
- FIPS 201
- NIST SP 800-76
- DoD 8520
- NIST SP 800-207 Zero Trust
Architecture designed for alignment with federal identity and biometric standards. Formal validation scoped during pilot engagement.
Data Protection
Encryption standards — no ambiguity
🔒
At Rest
AES-256-GCM for all biometric template data and disaggregated key parts. Each key part independently encrypted at its storage location.
🔄
In Transit
TLS 1.3 for all API communication. Certificate pinning on mobile clients. No biometric data transmitted — only assertion tokens.
🔑
On Device
Hardware-backed storage: iOS Secure Enclave (Keychain) and Android TEE (Keystore). Key Part 3 never leaves hardware security boundary.
- AES-256-GCM
- TLS 1.3
- FIPS 140-2 validated modules
- FIPS 140-3 (roadmap)
- CNSA 2.0 ready
Uses FIPS 140-2 validated cryptographic libraries (Apple CryptoKit, Android Keystore). Full FIPS 140-3 module validation scoped for pilot phase. Architecture supports CNSA Suite 2.0 cipher selection for NSS environments.
Integration
Auth broker — layers on top of existing systems
Enterprise System
→
"Sign in with BioTone"
→
Biometric Capture
→
Verify (on-device)
→
Token Returned
🔑
Identity Providers
Entra ID (live today)
Okta + Ping (near-term)
Standard OIDC / SAML
🪪
CAC / PIV
Complementary factor alongside physical credentials
📡
Tactical Edge
Offline-capable with cached credentials
Customer deploys our server software on their infrastructure. Data and liability stay with the customer.
Zero Trust
Continuous re-authentication — not just point of entry
Session confidence decays over time. Multi-signal architecture enables tiered re-verification from passive to active.
Tier 0 — Passive
Ambient
Face presence + PPG pulse detected in background. No user action.
Tier 1 — Micro
~2 sec
Voice micro-challenge. "Say continue." Voiceprint matched on-device.
Tier 2 — Light
~10 sec
PPG tap + voice code. Confirms liveness and identity before elevated actions.
Tier 3 — Full MFA
~30 sec
All 4 identity factors + PPG liveness. Session start or highest-risk actions.
Policy-configurable per security context. SCIF, enterprise, and tactical edge each get the cadence their threat model requires.
Deployment
Flexible deployment for any environment
🏢
Enterprise On-Premises
Customer-hosted backend on government or corporate infrastructure. Full data sovereignty.
☁️
Government Cloud
Azure Gov, AWS GovCloud, or customer-specified environment at IL5. FedRAMP High / GCC High on roadmap.
⛰️
Tactical Edge
On-device verification with locally cached credentials. Trades disaggregation for offline capability. Policy-controlled session limits. Syncs when connected.
📲
BYOD / Shared Facility
Device enrollment binds identity to a specific phone. Re-enrollment required for device change.
Proof of Concept
Working PoC — ready for evaluation
✓Enrollment across all 5 biometric signals with quality gates
✓Verification with per-signal match scoring and pass/fail
✓Score fusion with weighted majority decision engine
✓Liveness gating — selfie challenges + PPG pulse detection
✓Results dashboard — per-signal status, aggregate score, history
✓Multi-subject management with per-subject template isolation
✓iOS + Android — installable on test devices today
✓Admin dashboard — web console for subject and capture management
Timeline from PoC to pilot is driven by customer requirements. We move at your pace.
BioTone
Multi-Signal Biometric Identity
Five biometrics. One smartphone. Zero specialized hardware.
Roger Ach
CEO, BioTone Corporation
Benjamin Portman
CTO, Engineering Lead
Confidential — shared for evaluation purposes
