The Challenge
Post-quantum cryptographic authentication combines multiple heavyweight operations that traditionally create latency problems:
- Fully Homomorphic Encryption (FHE) — Lattice-based encryption resistant to quantum attacks
- ZK-STARK Proofs — Zero-knowledge verification without exposing biometric data
- Biometric Verification — Template matching with cryptographic attestation
- Regulatory Compliance — SOC2, PCI-DSS, and emerging quantum-readiness standards
Each of these operations is computationally expensive on its own. Combined, they create a stack that would normally be too slow for high-frequency use cases like institutional trading.
"Quantum-grade security at microsecond latency—that's what Cachee delivers."
The Solution
Cachee's intelligent caching layer sits between the application and the cryptographic stack, delivering previously-computed authentication results in nanoseconds while maintaining full security guarantees.
Authentication Flow
Cache hits bypass expensive cryptographic operations entirely
Key Technical Decisions
- Self-invalidating cache keys — Keys incorporate salt dates and circuit versions, automatically expiring when security parameters rotate
- Five-event invalidation — Biometric updates, key rotations, circuit upgrades, fraud detection, and compliance holds all trigger instant cache purges
- Zero-knowledge preservation — Cached proofs contain no biometric data—only cryptographic attestations
- Cache warming — 10,000 entries pre-loaded in 86ms at startup, eliminating cold-start latency
Benchmark Results
| Metric | Redis Alone | With Cachee | Improvement |
|---|---|---|---|
| Cache Latency | 231 µs | 1.21 ns | 190,909x faster |
| Throughput | 5,103 ops/sec | 827M ops/sec | 162,199x higher |
| 1M Requests | 3 min 16 sec | 1.2 ms | 163,333x faster |
| 1B Requests | 54.4 hours | 1.2 seconds | 163,200x faster |
| Network Dependency | 100% | 0% (L1 hits) | Eliminated |
ZK-STARK Proof Caching
| Metric | Re-Verification | Cachee Lookup | Improvement |
|---|---|---|---|
| Latency | 815 ms | 2.09 ns | 497,120,061x faster |
| 1M Proof Lookups | 9.4 days | 2 ms | Skip 815ms compute each |
Quantum-grade security at microsecond latency. Cachee makes post-quantum cryptography practical for real-time, high-frequency applications.
Business Impact
Cost Efficiency
By caching cryptographic operations, the firm reduced compute costs by 99.98%. Each authentication that would have required expensive FHE and ZKP computation now resolves from cache at negligible cost.
| Metric | Value |
|---|---|
| Compute cost per auth (cached) | $0.000000031 |
| Compute cost per auth (uncached) | $0.0002 |
| Cost reduction | 99.98% |
| Daily capacity at peak | 35 billion auths |
Competitive Advantage
The firm now offers quantum-secured authentication to their institutional clients as a premium feature—turning a cost center into a revenue driver. Their trading desks operate with both the strongest security posture and the lowest latency in their market segment.
Technical Deep Dive
Why Traditional Approaches Failed
Previous attempts to optimize the authentication stack focused on:
- Hardware acceleration — GPUs reduced ZKP proving time but couldn't break the 100µs barrier
- Algorithm optimization — Lighter-weight proofs compromised security guarantees
- Batch processing — Helped throughput but increased individual latency
Cachee's insight: most authentications are repeated. The same user, same device, same biometric template authenticates hundreds of times per day. Computing the cryptographic proof once and caching the result preserves full security while eliminating redundant computation.
Security Guarantees
Cached entries contain only:
- Cryptographic attestation (proof that verification succeeded)
- Timestamp and expiration
- Circuit version and salt identifier
No biometric data, no encryption keys, no sensitive parameters are ever cached. Even if the cache were compromised, attackers would gain no usable information—the zero-knowledge property is preserved.
Implementation Timeline
- Week 1 — Integration with existing auth stack (one SDK import)
- Week 2 — Cache key structure design and invalidation rules
- Week 3 — Load testing and performance validation
- Week 4 — Production rollout with monitoring
Total implementation time: 4 weeks from kickoff to production.