Trust Score Engine: Real-Time Risk Assessment in 20.8µs

Authentication is binary. Trust is continuous. A simple "authenticated" or "not authenticated" answer ignores crucial context: Is this user behaving normally? Is this device recognized? Is this location expected? Is the request pattern suspicious?

H33's Trust Score Engine answers these questions in 20.8 microseconds—fast enough to run on every request without impacting latency.

The Trust Score Pipeline

Every authentication request flows through a five-stage pipeline that evaluates multiple risk signals:

What Gets Evaluated

The trust score incorporates multiple signal categories:

• Device fingerprint: Hardware characteristics, browser configuration, installed fonts
• Behavioral biometrics: Typing patterns, mouse movements, touch pressure
• Location context: IP geolocation, timezone consistency, travel velocity
• Session patterns: Request frequency, API usage patterns, time-of-day
• Historical baseline: Deviation from user's established patterns

Benchmark Results

January 2026 benchmarks show each component running well under target:

Using Trust Scores

Trust scores enable adaptive security policies:

const result = await h33.auth.fullStack({
  userId: 'user_123',
  biometric: faceData,
  mode: 'turbo'
});

// Trust score: 0.0 (suspicious) to 1.0 (trusted)
if (result.trustScore < 0.5) {
  // Require step-up authentication
  await requireMFA(user);
} else if (result.trustScore < 0.8) {
  // Log for review, allow access
  auditLog.flag(result);
} else {
  // High trust, proceed normally
}

Privacy-Preserving Design

Trust scoring runs entirely on encrypted data using FHE:

• No raw biometrics stored: Only encrypted feature vectors
• No behavioral logs: Patterns computed on-the-fly from encrypted signals
• No location history: Only encrypted deviation scores
• Zero-knowledge compatible: Prove trust level without revealing signals

Even H33 can't see the signals that produce your trust score—we only see the encrypted computation results.