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Streaming Fraud Prevention

660,000 fake streams per day.
We end that.

Cryptographic infrastructure that makes streaming fraud mathematically impossible — not just detectable.

192 bytes
Device proof size
16ms
Proof generation
<1µs
Verification latency
Zero
Fake devices possible
Schedule Demo See the Architecture

$2B+ lost annually.
Every solution so far has failed.

Bot farms. Fake accounts. Artificial plays. Click farms running thousands of headless browsers 24/7. The scale is industrial.

Current defenses rely on behavioral heuristics, post-event analysis, and pattern matching. All of them share the same fatal flaw: they detect fraud after it happens. And all of them are bypassable.

Heuristics can be mimicked. Patterns can be randomized. Post-event analysis means the damage is already done.

Detection is not prevention. The industry needs prevention.

What exists today

Behavioral analysis. IP reputation. Listening-time heuristics. All reactive. All bypassable. Fraud farms adapt faster than detection models update.

What H33 provides

Cryptographic device attestation. Encrypted biometric identity. Proof-of-work bot prevention. Encrypted content classification. Four layers of prevention, not detection.

Four layers of prevention

Not detection. Prevention. Each layer makes a different class of fraud mathematically impossible.

Layer 1

DeviceProof — STARK Device Attestation

Every stream gets a 192-byte STARK proof bound to a real device. Hardware fingerprint, network jurisdiction, endpoint integrity. Verified in under 1 microsecond.

Bot farms running headless browsers cannot produce valid proofs. The proof requires a physical device with verified hardware state. 16ms to generate. Fits in an HTTP header.

192 bytes

Per-stream proof · 16ms generation · <1µs verification

Layer 2

Biometric Identity on Upload

Artist identity verified through FHE-encrypted biometrics. The platform never sees the raw biometric data. The system returns a cryptographic yes or no.

Cannot create fake artist accounts when each requires a verified unique human. No synthetic identities. No duplicate registrations. One real person per artist profile.

2.29M auth/sec

Encrypted biometric throughput · 35.25µs per auth

Layer 3

BotShield — Proof-of-Work Stream Protection

Proof-of-work challenge on every play request. Invisible to real users on real devices. Bots burn compute at scale — economically unviable.

The cost to fake one stream exceeds the revenue from that stream. At bot-farm scale, the economics collapse entirely. A single script tag deploys it.

Sub-ms

Challenge-response for real devices · Invisible to users

Layer 4

Encrypted Content Classification

Encrypted ML classifies whether audio is AI-generated versus human-performed. The model runs on ciphertext. The platform never accesses raw audio.

Privacy-preserving detection of synthetic content. No raw audio leaves the encryption boundary. The classification result is a signed attestation, not an opinion.

Ciphertext

Classification on encrypted audio · Zero plaintext exposure

How it integrates

No platform rebuild required. H33 fits into existing infrastructure.

Stream request arrives
   DeviceProof verified from HTTP header (<1µs)
   BotShield proof-of-work validated (sub-ms)
   Stream plays
   H33-74 attestation committed (42µs)

Artist upload arrives
   Biometric identity verified (35.25µs)
   Encrypted ML classifies content on ciphertext
   Upload accepted with signed attestation

Every stream is provable

Every stream, upload, and play event produces an H33-74 attestation — 74 bytes, post-quantum signed, independently verifiable. Three independent hardness assumptions: MLWE lattices, NTRU lattices, and hash-based signatures.

Labels, distributors, auditors, and regulators can verify any stream's authenticity without trusting the platform. The proof is mathematical, not behavioral. It does not degrade. It does not have false positives.

1. Device sends stream request with DeviceProof header
2. BotShield validates proof-of-work
3. Stream plays on verified device
4. Event signed (post-quantum, three independent hardness assumptions)
5. H33-74 attestation committed — 74 bytes, permanent, independently verifiable

Any party can verify. Labels do not need to trust the platform. Distributors do not need to trust the label. Regulators do not need to trust anyone. The cryptographic proof is self-verifying. 7 patents pending. 300+ claims.

Measured performance

Production numbers. Sustained. Independently reproducible.

ComponentLatencyDetail
DeviceProof generation16ms192-byte STARK proof bound to device hardware
DeviceProof verification<1µsServer-side, fits in request pipeline
Biometric auth35.25µs2.29M auth/sec sustained · FHE-encrypted
BotShield challengeSub-msProof-of-work · invisible to real users
H33-74 attestation42µs74 bytes · post-quantum signed · per stream

Zero user-perceived latency. DeviceProof generates while the page loads. BotShield runs in the background. Biometric verification happens once at upload. H33-74 attestation commits after the stream starts. The listener notices nothing.

What streaming fraud looks like after H33

Bot farms

Cannot produce valid DeviceProof. Headless browsers lack hardware attestation state. Every fake stream is rejected before it plays.

Fake accounts

Cannot pass encrypted biometric verification. One verified human per artist profile. Synthetic identities are cryptographically impossible.

Click farms

BotShield proof-of-work makes bulk streaming economically unviable. The compute cost to fake streams exceeds the revenue they generate.

AI-generated content fraud

Encrypted ML classification detects synthetic audio without accessing the raw content. The platform cannot be used to launder AI-generated music as human-performed.

Verify It Yourself