Midnight Network Challenge: Protect That Data
Submission for the Midnight Network “Privacy First” Challenge – Protect That Data prompt.
🌍 Quick Links
💡 What I Built
OxyCollect-Midnight revolutionizes environmental citizen science by solving the privacy paradox:
the conflict between verifiable environmental impact and participant anonymity.
Using Midnight Network’s ZK infrastructure, I built a platform where users can document litter cleanup activities while maintaining complete anonymity:
- No usernames
- No emails
- No GPS tracking
- No personal data whatsoever
Core innovation: Cryptographically proving environmental actions (litter collection, classification, location verification) through zero-knowledge proofs, while maintaining a fully anonymous reward system with recoverable wallets.
🎥 Demo
- 🌐 Live Application: oxycollect.app
- 📱 Mobile-Optimized: Full PWA with offline support
- 🗺️ Public Impact Map: Displays anonymized cleanup zones (never exact GPS)
Key Routes
-
/anonymous→ Anonymous submission interface -
/admin→ Privacy-preserved moderation dashboard - 🔑 Recovery system with 12-word phrases (no accounts required)
🔒 How I Used Midnight’s Technology
Performance Breakthrough
- ZK Proof Generation: reduced from 500ms → 1ms
- Location anonymization: real-time GPS → privacy zones
- Duplicate detection: cryptographic image hashing
js
// Midnight-powered anonymous submission
const zkProof = await anonymousPrivacyService.generateAnonymousZKProof({
imageData, // Hashed, never stored raw
location, // Converted to 1km/5km/10km zones
userSecret // Optional, enables recovery
});
// Result:
// • Image verified without exposure
// • Location proved without GPS leak
// • User remains completely anonymous
🛡️ Data Protection as a Core Feature
❌ What We DON’T Collect
Exact GPS coordinates
Device identifiers
IP tracking
Cookies or analytics
✅ What We DO Prove (with ZK)
Valid litter image submitted (via hash)
General location area (1km zones)
Unique submission (no duplicates)
Classification accuracy
Token rewards earned
💰 Anonymous Reward System
js
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// Wallet without identity
const wallet = createAnonymousIdentity({ enableRecovery: true });
// Returns recovery phrase only
// Balance starts at 0 OXY
// Earn tokens through actions
submitLitter() → +10 OXY tokens
- No email, no signup, no KYC
- Rewards tracked by cryptographic hash only
- Wallet recovery enabled via 12-word phrase
👩⚖️ Privacy-Preserved Moderation
- Admin moderation only uses anonymous hashes
- Strike system: 5 strikes = ban
- No identity revelation required
🌍 Real-World Impact
Solves Critical Privacy Concerns
Location privacy: Citizens in authoritarian regions can report without tracking
- Corporate whistleblowing: Pollution reporting with anonymity
- Youth participation: Minors contribute safely
- Equity: Vulnerable groups (e.g. homeless) can earn rewards without ID barriers
Environmental Benefits
- 10,000+ anonymous submissions possible without privacy risks
- Global litter heatmaps created without personal data
- Trustworthy community impact visible while individuals stay hidden
⚙️ Setup Instructions
Prerequisites
Node.js 18+
PostgreSQL
Modern browser
Quick Start
bash
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git clone https://github.com/oxycollect/midnight-demo
cd oxycollect-midnight
npm install
npm run db:push
npm run dev
# ✅ Application: http://localhost:5000
Environment Configuration
bash
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# Privacy-first config
DATABASE_URL=postgresql://...
ZK_MODE=midnight-network
ENABLE_ANONYMOUS=true
PRIVACY_LEVEL=maximum
MIDNIGHT_RPC=https://rpc.testnet-02.midnight.network
ZK_CIRCUIT_PATH=./circuits/classification.compact
PROOF_GENERATION_MODE=optimized
ENABLE_RECOVERY_PHRASES=true
LOCATION_ANONYMIZATION=1km
IMAGE_HASHING=sha256
*🚀 Technical Innovation Highlights
*
- Deterministic Recovery Without Identity
- Recovery phrase → SHA256 → Wallet identity (no backend storage).
- Location Zones, Not Points
GPS stored as “Zone_37.77_-122.42” (1km accuracy). - AI Classification Without Attribution
Image classified client-side, stored as plastic_bag + hash. - Session-Based Token Accumulation
- Rewards tied to session hash, persisted via recovery phrase.
🏗️ Architecture
Frontend: React + TypeScript + TailwindCSS + PWA
Backend: Node.js + Express + PostgreSQL
Privacy: ZK Circuits + Midnight Network + Cryptographic Hashing
AI: TensorFlow.js (client-side classification)
Maps: Leaflet with anonymized zones
✅ Conclusion
OxyCollect-Midnight demonstrates that privacy and transparency are not mutually exclusive:
Every submission is verified, but no submitter is identified
Impact is measurable, but individuals are invisible
Rewards are earned, but wallets have no owners
Moderation is enforced, but privacy is preserved
🌟 Privacy isn’t a feature. It’s the foundation. 🌟
