Security & Reputation Systems
To maintain integrity across decentralized AI execution and RWA revenue automation, Hubic implements a layered security framework. This combines real-time zk-proof enforcement, slashing conditions, and on-chain reputation metrics — forming a self-regulating trust system.
🛡️ Risk Mitigation Matrix
Faulty Inference
zk-proof validation enforced by verifier contracts
Lazy Validators
Automatic slashing of HUB for missed validations
Executor Downtime
Dynamic reassignment using smart contract task requeue
Model Spoofing
zkRegistry prevents unverified or tampered model usage
Collusion Behavior
Multi-node challenge + dispute resolution protocol
📊 Reputation Layer
Every compute actor — executor, validator, or agent — has an on-chain reputation score, based on cryptographically provable performance:
Uptime
Number of tasks completed vs missed
Proof Accuracy
zk-proof pass/fail ratio
Latency & SLA Adherence
Execution timestamps + event logs
Dispute Outcomes
Challenge resolution win/loss history
RWA Yield Efficiency
Inference-to-revenue ratio (for monetized models)
🧩 Integration with Protocol Logic
Staking Weighting: High-reputation actors get higher task routing priority and slashing protection.
Governance Influence: DAO voting rights may be boosted for agents or validators with strong historical accuracy.
Dynamic Reward Multipliers: Protocol bonuses scale with verified contribution quality.
🌍 RWA Impact:
Revenue Routing Based on Trust: Only models/agents with clean reputation earn RWA-based income.
Transparent Yield Quality: RWA token holders can validate performance history before investing.
Compliance Friendly: All data is verifiable and timestamped, allowing integration with legal reporting or off-chain attestations.
Trust in Hubic is not reputation by hearsay — it’s mathematically proven, stake-weighted, and economically enforced.
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