Healthcare systems verify identity, authorization, and clinical data by exposing Protected Health Information. Post-quantum cryptographic caching changes that. Proof-based trust replaces exposure-based trust.
Every clinical system today verifies by exposing. To check a patient's allergy before prescribing, the system fetches the full allergy list — exposing every allergy to the cache layer, the network, and every intermediate service. To verify insurance eligibility, the system pulls the patient's full coverage record. To check drug interactions, the system reads the complete medication list.
This model worked when cache infrastructure was trusted internal plumbing. But two shifts make it unsustainable:
NIST PQ migration (CNSA 2.0, deadline 2030) replaces 64-byte Ed25519 signatures with 3,309-byte ML-DSA-65 signatures. Cached session tokens, certificates, and signed clinical data grow 50x. Redis latency scales linearly with payload — at 3,309 bytes, each read costs 440us instead of 310us. At 100K clinical lookups per second, that's 44 CPU-seconds of blocking per wall-clock second.
Clinical AI systems — radiology assist, sepsis prediction, drug interaction engines — cache inference results for performance. But cached AI outputs are ePHI under HIPAA. A cached radiology classification is a medical record. A cached sepsis risk score is a clinical judgment. These need audit trails, provenance, and tamper-evidence. Redis provides none.
Redis stores every cached value in plaintext memory. No encryption at rest. No per-key access controls. No audit trail of who read what. No integrity verification. If an attacker accesses Redis memory — through a compromised sidecar, a shared VPC, or a memory dump — every cached patient record, session token, and clinical result is exposed in cleartext.
ElastiCache adds EBS encryption (disk-level), but memory is still plaintext. The "encryption at rest" marketing claim doesn't protect in-memory data. And neither Redis nor ElastiCache can answer the question every HIPAA auditor asks: "Can you prove this cached value hasn't been modified since it was stored?"
HIPAA 45 CFR 164.312(b) requires "audit controls" — mechanisms to record and examine access to ePHI. Your database has audit logging. Your application has access logs. But your cache? Redis has zero audit capability. Every cached ePHI read is unlogged, untracked, and unverifiable. That's a finding waiting to happen.
Cachee changes the verification model. Instead of exposing PHI to verify it, Cachee stores signed, fingerprinted computation results that can be verified without reading the underlying data.
Three independent post-quantum signature families (ML-DSA-65, FALCON-512, SLH-DSA) sign every cached entry. Modification is detectable. Authenticity is provable. No trust assumption required.
SHA3-256(input_hash || computation_hash || parameter_hash || version || hardware_class) — the fingerprint binds every result to its exact inputs. Change the patient record, the model version, or the parameters, and the fingerprint invalidates. Stale clinical data cannot be served.
Tamper-evident audit log. Every read, write, and state transition is recorded with the hash of the previous entry. Delete an entry? Detectable. Modify an entry? Detectable. Reorder entries? Detectable. HIPAA 164.312(b) satisfied by architecture, not by add-on logging.
AUDITLOG reconstructs any cached value's full lifecycle from creation to current state. "What was in cache at 2:00 PM last Tuesday?" is one command. Temporal versioning meets HIPAA's 6-year retention requirement with cryptographic proof, not just database backups.
PHI integrity is no longer a policy. It's a mathematical property of the storage layer.
Run it yourself: brew install cachee && cachee-gold-demo
Prove a drug interaction check was performed without exposing the patient's medication list. The computation fingerprint proves the check happened. The signature proves the result is authentic. The underlying PHI stays encrypted.
Every cached AI clinical output carries provenance: which model, which version, which training data, which input produced this result. When the EU AI Act or FDA requires traceability for clinical AI decisions, the audit trail is already built into the cache layer.
CNSA 2.0 mandates PQ migration by 2030 for federal systems. Healthcare systems touching Medicare, VA, or federal programs will need PQ-signed credentials. Cachee is already PQ-native — no migration required. Every entry signed by FIPS 204 (ML-DSA-65) and FIPS 205 (SLH-DSA) today.
Reconstruct the exact state of any cached clinical data at any point in time. When a malpractice case asks "what did the system show the physician at 2:14 PM?", the answer is one command: AUDITLOG. Tamper-evident. Independently verifiable. Admissible.
| HIPAA Requirement | CFR Reference | Cachee Implementation |
|---|---|---|
| Access controls | 164.312(a) | Owner/Regulator/Auditor key types + AUTH enforcement |
| Audit controls | 164.312(b) | Hash-chained audit log, Merkle anchoring, AUDITVERIFY |
| Integrity controls | 164.312(c) | 3 PQ signatures per entry, computation fingerprint |
| Person authentication | 164.312(d) | SHA3-256 key validation, per-key permissions |
| Transmission security | 164.312(e) | In-process (zero network exposure for reads) |
One architecture. Many manifestations.
Deploy Cachee in your VPC. PHI never leaves your boundary.
Every value signed. Every access audited. Every result replayable.