67x Proof Cache Speedup:
Intelligent Cryptographic Caching

Cryptographic proof verification is computationally intensive. But most applications repeatedly verify the same types of proofs for the same users. H33's intelligent proof caching eliminates this redundancy, delivering 67x faster verification for cached proofs.

How It Works

When H33 verifies a ZK proof, we don't just validate and discard—we extract a cryptographic fingerprint and cache it:

• Proof fingerprinting: Each proof gets a unique, collision-resistant identifier
• Validity window: Cached proofs remain valid for configurable duration
• Context binding: Cache entries are bound to user, device, and session context
• Secure invalidation: Any context change automatically invalidates cached entries

Security Guarantees

Caching doesn't compromise security. Our cache system maintains full cryptographic guarantees:

• No proof reuse attacks: Cache entries include nonces and timestamps
• Tamper detection: Any modification invalidates the cache entry
• Context isolation: Users cannot access each other's cached proofs
• Automatic expiration: Stale entries are cryptographically invalidated

// Cache-aware verification
const result = await h33.proof.verify({
  proof: userProof,
  cachePolicy: {
    enabled: true,
    maxAge: '1h',
    contextBinding: ['userId', 'deviceId']
  }
});

// First call: full verification
// Subsequent calls: cache hit (67x faster)

Cache Architecture

H33's proof cache is a multi-tier system optimized for different access patterns:

• L1 (In-memory): Hot proofs from active sessions—sub-microsecond access
• L2 (Redis): Recent proofs across the cluster—microsecond access
• L3 (Persistent): Long-term proof history for audit trails

Smart prefetching predicts which proofs will be needed and warms the cache proactively.

When to Use Caching

Proof caching is most effective for:

• Session-based applications: Users authenticate once, then perform many actions
• Real-time systems: Games, collaboration tools, trading platforms
• Mobile applications: Where every millisecond of battery life matters
• High-frequency verification: API rate limiting, access control checks

Performance Impact

In typical applications where 80-90% of verifications are for returning users, proof caching delivers dramatic improvements:

• Average latency: Reduced by 60-65%
• P99 latency: Significantly more consistent
• Throughput: Increased by 40-50%
• CPU usage: Reduced by 50-60%

These aren't theoretical numbers—they're measured across our production infrastructure.