Emission Shield

EmissionShield — Emission Manipulation Firewall for Bittensor

Bittensor allocates TAO emissions through validator consensus, but this mechanism is vulnerable to collusion, stake centralization, and reward capture loops. There is no systematic way to detect or quantify these risks today.

EmissionShield is a dedicated subnet that acts as a cryptoeconomic immune system. It continuously monitors metagraph state across all subnets and produces four mathematically rigorous risk metrics:

• ECI (Emission Capture Index) — measures emission concentration using Shannon entropy
• VIS² (Validator Influence Score) — detects disproportionate validator weight deviation
• SEM (Stake Entropy Metric) — quantifies stake centralization risk
• SRI (Subnet Risk Index) — aggregated risk score combining all signals

Miners operate as anomaly analysts — they analyze validator weight correlations, detect temporal emission drift using CUSUM/EWMA, identify abnormal reward clustering, and generate risk predictions. Validators cross-verify miner reports and score them on precision, recall, timeliness, and novelty.

The subnet outputs structured risk reports that integrate directly with Bittensor governance — enabling evidence-based Senate proposals, automated threshold alerts, and validator accountability.

EmissionShield does not enforce penalties. It produces verifiable evidence. Governance decides.

Built with Python. Includes working simulation demonstrating detection of injected collusion patterns.

GitHub: github.com/karagozemin/EmissionShield
Pitch Deck: https://emission-distortion-the--xp6qyim.gamma.site

We designed and built EmissionShield from scratch during this hackathon. Here is what we accomplished:

Research & Problem Definition
— Identified five core emission manipulation vectors in Bittensor: validator collusion, emission concentration, stake centralization, reward capture loops, and sybil subnet farming.

Metric Design
— Defined four mathematically rigorous, bounded, deterministic metrics (ECI, VIS², SEM, SRI) using Shannon entropy, emission-weighted variance, and graph cycle analysis. All formulas are fully specified with edge cases documented.

Subnet Architecture
— Designed a three-layer architecture (Data Ingestion → Analysis Engine → Output Layer) with clearly defined miner and validator roles, communication protocols, and timing specifications.

Miner & Validator Logic
— Implemented four miner analysis pipelines (weight correlation, temporal drift via CUSUM/EWMA, reward clustering, risk prediction) and a full validator verification pipeline with precision/recall/timeliness/novelty scoring.

Incentive & Economic Model
— Designed a complete incentive mechanism with cost-of-attack analysis for five attack vectors. Demonstrated that honest participation is the dominant strategy.

Governance Integration
— Designed threshold-based alert system, Senate proposal evidence format, and recursive self-monitoring capability.

Simulation
— Built a working Python simulation that generates synthetic healthy vs. manipulated subnets and demonstrates EmissionShield correctly distinguishing between them. Includes 4-panel visualization output.

Documentation
— Produced full technical documentation: architecture deep-dive, economic model, metric specifications, and governance design — totaling 3000+ lines across 13 files.

Not now