22. 🔒 Conneth Anti-Scam System
Overview: The Conneth Anti-Scam System is designed to protect users and preserve trust in a decentralized communication environment. Traditional platforms rely on centralized moderation and identity verification. Conneth uses a Web3-native approach powered by Proof-of-Connection (PoC), Trust Ratings, and DAO-driven moderation, ensuring a safer, more transparent digital space.
🛡️ Key Features
1. Proof-of-Connection (PoC) Requirement All communication and earning activities (calls, messages, cloud hosting) are tied to verified wallet identities. Only users who complete mutual PoC can fully interact, reducing fake or anonymous abuse.
2. Connection History Ledger Each wallet builds a public “connection graph” of real interactions. Suspicious wallets with zero meaningful PoC history can be flagged or limited in reach.
3. Trust Rating Score Each user has a dynamic score based on:
Verified PoC interactions
Time-active in the network
DAO reputation endorsements
Past behavior (flagged for scam, spam, impersonation, etc.)
4. Wallet-based Reporting System Any user can flag messages or calls as scams or harassment. Reports are reviewed by trusted community moderators elected through DAO voting. Penalties may include cooldowns, temporary bans, or Trust Rating reduction.
5. Community Moderation & DAO Governance Moderators are empowered to take action on verified abuse reports. They are rewarded in $CONN for handling cases fairly. All moderation actions are logged on-chain for transparency.
6. Blacklist Integration & Warnings Conneth integrates with public scam wallet blacklists. If a blacklisted address attempts contact, users receive instant warnings with options to block or report.
7. Behavioral Detection Filters (Coming Soon) Using AI-assisted heuristics, Conneth will identify patterns like mass messaging, link spam, or impersonation attempts, alerting moderators in real time.
🤝 Why It Matters
In Web3, where users are pseudonymous, scams can spread rapidly. Conneth doesn’t rely on KYC or centralized databases — it uses Proof, Transparency, and Community Power to create a trusted ecosystem where real people connect and earn, while scammers are stopped at the door.
Subpages:
Trust Score Logic
Explains how scores are calculated
Includes formulas, variables (PoC count, flags, endorsements)
Example scenarios: how scores increase/decrease
DAO Moderation Process
Role of elected moderators
Case handling steps
Rewards, penalties, and on-chain transparency
Connection History Ledger
Visual example of how connection graphs prevent abuse
Flagging low-trust, zero-history wallets
Wallet-based Reporting
Flow diagram of report-to-review process
What happens after a user flags someone
Scam Wallet Blacklist Integration
Explanation of blacklist sources
Warning system UX
Block/report functions
Behavioral Detection Filters (Coming Soon)
AI-based heuristics to identify spam/scam bots
Real-time moderator alerts
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