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Dave 693ce3fafe Added some crazy AI generated ideas, as a brainstorming exercise.

2025-06-12 15:06:34 -04:00

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Use Case 4: Sybil-Resistant Identity Networks

The Identity Problem in Web3

Decentralized systems face a fundamental challenge: how to establish identity and reputation without central authorities while preventing Sybil attacks.

Current Identity System Failures

Centralized Identity Providers
- Single points of failure (KYC providers, social logins)
- Privacy violations through data aggregation
- Censorship and deplatforming risks
- Geographic and political exclusion
Token-Based Sybil Resistance
- Plutocratic (wealthy users have more influence)
- Doesn't represent real human relationships
- Vulnerable to borrowing/renting attacks
- Excludes users without capital
Proof of Personhood Ceremonies
- Require synchronous participation
- Exclude users in certain timezones
- Technical barriers for non-technical users
- Still vulnerable to sophisticated attacks

The BFT-CRDT Identity Solution

A web of trust that grows organically through attestations, resistant to Sybil attacks through social graph analysis:

Traditional Identity:
[Central Authority] → [Identity Verification] → [Single Identity Record]
         ↓                      ↓                        ↓
   [Can be hacked]    [Privacy violation]        [Can be revoked]

BFT-CRDT Identity Network:
[User A] ←→ [User B]
    ↓    ×    ↓
[User C] ←→ [User D]
    ↓
[Attestations merge via CRDT]
    ↓
[Emergent trust graph]

Key Innovation: Trust Without Consensus

No global agreement on who is "verified"
Each participant maintains their own trust graph
Applications interpret the graph based on their needs
Sybil resistance emerges from graph topology

Architecture

Core Data Structures

pub struct IdentityCRDT {
    // All attestations in the network
    attestations: Map<AttestationId, Attestation>,
    
    // Revocations (tombstones)
    revocations: Set<AttestationId>,
    
    // Computed trust paths
    trust_cache: TrustCache,
    
    // Anti-Sybil metrics
    sybil_scores: Map<IdentityId, SybilScore>,
}

pub struct Attestation {
    pub id: AttestationId,
    pub issuer: IdentityId,
    pub subject: IdentityId,
    pub claim_type: ClaimType,
    pub claim_value: ClaimValue,
    pub confidence: u8, // 0-100
    pub context: AttestationContext,
    pub timestamp: Timestamp,
    pub expiry: Option<Timestamp>,
    pub signature: Signature,
}

pub enum ClaimType {
    // Social attestations
    KnowsPersonally,
    MetInPerson,
    WorkedWith,
    FamilyMember,
    
    // Skill attestations
    TechnicalSkill(String),
    ProfessionalRole(String),
    EducationCredential(String),
    
    // Behavior attestations
    TrustedTrader,
    ReliableCounterparty,
    GoodCitizen,
    
    // Verification attestations
    VerifiedEmail(Hash),
    VerifiedPhone(Hash),
    VerifiedAddress(Hash),
    BiometricHash(Hash),
}

pub struct AttestationContext {
    // Where/how the attestation was made
    pub location: Option<Location>,
    pub event: Option<String>,
    pub proof_of_interaction: Option<InteractionProof>,
    pub metadata: Map<String, String>,
}

Trust Computation

impl IdentityCRDT {
    // Calculate trust between two identities
    pub fn calculate_trust(
        &self,
        source: IdentityId,
        target: IdentityId,
        claim_type: ClaimType,
        params: TrustParams,
    ) -> TrustScore {
        // Find all paths from source to target
        let paths = self.find_trust_paths(source, target, params.max_depth);
        
        if paths.is_empty() {
            return TrustScore::Unknown;
        }
        
        // Weight paths by:
        // - Length (shorter = better)
        // - Attestation confidence
        // - Recency
        // - Path diversity
        let weighted_scores: Vec<f64> = paths
            .iter()
            .map(|path| self.score_path(path, claim_type, params))
            .collect();
        
        // Aggregate using params.aggregation_method
        let final_score = match params.aggregation_method {
            AggregationMethod::Maximum => weighted_scores.max(),
            AggregationMethod::Average => weighted_scores.average(),
            AggregationMethod::Median => weighted_scores.median(),
            AggregationMethod::WeightedByDiversity => {
                self.diversity_weighted_aggregate(paths, weighted_scores)
            }
        };
        
        TrustScore {
            value: final_score,
            confidence: self.calculate_confidence(paths.len(), weighted_scores.variance()),
            paths_found: paths.len(),
            computation_time: timestamp(),
        }
    }
    
    fn score_path(
        &self,
        path: &TrustPath,
        claim_type: ClaimType,
        params: &TrustParams,
    ) -> f64 {
        let mut score = 1.0;
        
        for edge in &path.edges {
            let attestation = &self.attestations[&edge.attestation_id];
            
            // Confidence factor
            score *= (attestation.confidence as f64) / 100.0;
            
            // Recency factor
            let age = timestamp() - attestation.timestamp;
            score *= params.recency_decay.decay_factor(age);
            
            // Claim type relevance
            score *= params.claim_relevance(attestation.claim_type, claim_type);
            
            // Penalize long paths
            score *= params.path_length_penalty.pow(path.edges.len());
        }
        
        score
    }
}

Sybil Resistance Mechanisms

pub struct SybilDetector {
    // Network topology analysis
    pub min_clustering_coefficient: f64,
    pub max_betweenness_centrality: f64,
    pub min_attestation_diversity: f64,
    
    // Temporal analysis
    pub min_account_age: Duration,
    pub max_attestation_rate: f64,
    
    // Behavioral analysis
    pub interaction_requirements: InteractionRequirements,
}

impl SybilDetector {
    pub fn analyze_identity(&self, id: IdentityId, graph: &IdentityCRDT) -> SybilScore {
        let mut score = SybilScore::default();
        
        // 1. Graph topology checks
        score.clustering = self.check_clustering(id, graph);
        score.centrality = self.check_centrality(id, graph);
        
        // 2. Attestation pattern checks
        score.attestation_diversity = self.check_attestation_diversity(id, graph);
        score.temporal_distribution = self.check_temporal_patterns(id, graph);
        
        // 3. Interaction proof checks
        score.interaction_quality = self.check_interactions(id, graph);
        
        // 4. Economic cost analysis
        score.attack_cost = self.estimate_attack_cost(id, graph);
        
        score
    }
    
    fn check_clustering(&self, id: IdentityId, graph: &IdentityCRDT) -> f64 {
        // Real social networks have high clustering
        // Sybil networks tend to be tree-like
        let neighbors = graph.get_neighbors(id);
        let interconnections = graph.count_edges_between(neighbors);
        let possible_connections = neighbors.len() * (neighbors.len() - 1) / 2;
        
        interconnections as f64 / possible_connections as f64
    }
}

Use Cases

1. Decentralized KYC/AML

pub struct DecentralizedKYC {
    required_attestations: Vec<RequiredAttestation>,
    trust_threshold: f64,
    approved_issuers: Option<Set<IdentityId>>,
}

pub struct RequiredAttestation {
    claim_types: Vec<ClaimType>,
    min_confidence: u8,
    max_age: Duration,
    min_paths: usize,
}

impl DecentralizedKYC {
    pub fn verify_identity(
        &self,
        identity: IdentityId,
        graph: &IdentityCRDT,
        verifier: IdentityId,
    ) -> KYCResult {
        let mut results = Vec::new();
        
        for requirement in &self.required_attestations {
            let attestations = graph.find_attestations(
                identity,
                &requirement.claim_types,
                verifier,
            );
            
            let valid_attestations = attestations
                .filter(|a| a.confidence >= requirement.min_confidence)
                .filter(|a| a.age() <= requirement.max_age)
                .filter(|a| self.is_approved_issuer(a.issuer))
                .collect::<Vec<_>>();
            
            results.push(RequirementResult {
                requirement: requirement.clone(),
                found: valid_attestations.len(),
                required: requirement.min_paths,
                passed: valid_attestations.len() >= requirement.min_paths,
            });
        }
        
        KYCResult {
            identity,
            passed: results.iter().all(|r| r.passed),
            details: results,
            timestamp: timestamp(),
        }
    }
}

2. Reputation-Based Governance

pub struct ReputationGovernance {
    // Different reputation types have different weights
    reputation_weights: Map<ClaimType, f64>,
    
    // Minimum reputation for participation
    participation_threshold: f64,
    
    // How reputation translates to voting power
    power_curve: PowerCurve,
}

impl ReputationGovernance {
    pub fn calculate_voting_power(
        &self,
        voter: IdentityId,
        graph: &IdentityCRDT,
        context: &GovernanceContext,
    ) -> VotingPower {
        let mut weighted_reputation = 0.0;
        
        // Aggregate different types of reputation
        for (claim_type, weight) in &self.reputation_weights {
            let reputation = graph.calculate_reputation(
                voter,
                claim_type.clone(),
                &context.reputation_params,
            );
            
            weighted_reputation += reputation.value * weight;
        }
        
        // Check participation threshold
        if weighted_reputation < self.participation_threshold {
            return VotingPower::Ineligible;
        }
        
        // Apply power curve (e.g., quadratic)
        let power = self.power_curve.apply(weighted_reputation);
        
        VotingPower::Eligible {
            power,
            reputation_score: weighted_reputation,
            calculation_method: self.power_curve.description(),
        }
    }
}

pub struct SocialRecovery {
    pub identity: IdentityId,
    pub recovery_threshold: usize,
    pub guardians: Vec<Guardian>,
    pub time_delay: Duration,
}

pub struct Guardian {
    pub identity: IdentityId,
    pub relationship: ClaimType,
    pub min_relationship_age: Duration,
    pub weight: u32,
}

impl SocialRecovery {
    pub fn initiate_recovery(
        &self,
        new_key: PublicKey,
        guardian_signatures: Vec<GuardianSignature>,
        graph: &IdentityCRDT,
    ) -> Result<RecoveryRequest> {
        // Verify guardians
        let mut total_weight = 0u32;
        let mut verified_guardians = Vec::new();
        
        for sig in guardian_signatures {
            // Check guardian is valid
            let guardian = self.guardians
                .iter()
                .find(|g| g.identity == sig.guardian)
                .ok_or("Unknown guardian")?;
            
            // Verify relationship still exists
            let relationship = graph.verify_relationship(
                self.identity,
                guardian.identity,
                guardian.relationship.clone(),
            )?;
            
            // Check relationship age
            if relationship.age() < guardian.min_relationship_age {
                return Err("Relationship too new");
            }
            
            // Verify signature
            sig.verify(&new_key)?;
            
            total_weight += guardian.weight;
            verified_guardians.push(sig.guardian);
        }
        
        // Check threshold
        if verified_guardians.len() < self.recovery_threshold {
            return Err("Insufficient guardians");
        }
        
        Ok(RecoveryRequest {
            identity: self.identity,
            new_key,
            guardians: verified_guardians,
            initiated_at: timestamp(),
            executable_at: timestamp() + self.time_delay,
        })
    }
}

4. Skill-Based Matching

pub struct SkillMarketplace {
    pub skill_graph: IdentityCRDT,
    pub matching_params: MatchingParams,
}

impl SkillMarketplace {
    pub fn find_providers(
        &self,
        seeker: IdentityId,
        required_skills: Vec<Skill>,
        preferences: MatchingPreferences,
    ) -> Vec<SkillMatch> {
        let mut candidates = Vec::new();
        
        // Find all identities with required skills
        for skill in &required_skills {
            let providers = self.skill_graph.find_by_claim(
                ClaimType::TechnicalSkill(skill.name.clone()),
                preferences.min_confidence,
            );
            
            for provider in providers {
                // Calculate trust path from seeker
                let trust = self.skill_graph.calculate_trust(
                    seeker,
                    provider.identity,
                    ClaimType::TechnicalSkill(skill.name.clone()),
                    preferences.trust_params.clone(),
                );
                
                // Check if meets minimum trust
                if trust.value >= preferences.min_trust {
                    candidates.push(SkillMatch {
                        provider: provider.identity,
                        skill: skill.clone(),
                        trust_score: trust.value,
                        attestations: provider.attestations,
                        estimated_rate: self.estimate_rate(&provider, skill),
                    });
                }
            }
        }
        
        // Sort by preference
        candidates.sort_by(|a, b| {
            preferences.ranking_function(a, b)
        });
        
        candidates
    }
}

Privacy Features

1. Selective Disclosure

pub struct PrivateAttestation {
    // Public part
    pub id: AttestationId,
    pub issuer: IdentityId,
    pub subject_commitment: Commitment,
    pub claim_type: ClaimType,
    pub timestamp: Timestamp,
    
    // Private part (revealed selectively)
    pub private_data: EncryptedData,
    pub reveal_key: Option<RevealKey>,
}

impl PrivateAttestation {
    pub fn reveal_to(&self, recipient: IdentityId) -> RevealToken {
        // Generate reveal token for specific recipient
        let token = RevealToken {
            attestation_id: self.id,
            recipient,
            expiry: timestamp() + Duration::hours(24),
            scope: RevealScope::FullClaim,
        };
        
        token.encrypt_for(recipient)
    }
}

2. Zero-Knowledge Proofs

pub struct ZKIdentityClaim {
    // Prove properties without revealing identity
    pub proof: ZKProof,
    pub public_inputs: PublicInputs,
    pub nullifier: Nullifier, // Prevent double-usage
}

impl IdentityCRDT {
    pub fn prove_reputation_threshold(
        &self,
        identity: IdentityId,
        threshold: f64,
        claim_type: ClaimType,
    ) -> ZKIdentityClaim {
        // Generate proof that reputation > threshold
        // without revealing actual reputation or identity
        let witness = self.gather_reputation_witness(identity, claim_type);
        let proof = generate_zk_proof(witness, threshold);
        
        ZKIdentityClaim {
            proof,
            public_inputs: PublicInputs { threshold, claim_type },
            nullifier: derive_nullifier(identity, timestamp()),
        }
    }
}

Implementation Guide

Starting an Identity Network

// 1. Initialize identity
const identity = new Identity({
    publicKey: await generateKeypair(),
    profile: {
        displayName: "Alice",
        avatar: "ipfs://...",
    },
});

// 2. Create initial attestations
await identity.attestTo({
    subject: "bob.eth",
    claimType: "KnowsPersonally",
    confidence: 95,
    context: {
        event: "ETH Denver 2024",
        proof: interactionProof,
    },
});

// 3. Join identity network
const network = new IdentityNetwork({
    bootstrapPeers: ["peer1", "peer2"],
    storage: new IPFSStorage(),
});

await network.publishIdentity(identity);
await network.syncAttestations();

Building Trust Relationships

// Organic trust building
async function buildTrust() {
    // 1. Attend events and meet people
    const eventAttestations = await collectEventAttestations("ETH Denver");
    
    // 2. Work on projects together  
    const projectAttestations = await collaborateOnProject({
        project: "DeFi Protocol",
        teammates: ["carol.eth", "dave.eth"],
        duration: "3 months",
    });
    
    // 3. Trade/interact on-chain
    const onChainAttestations = await generateFromOnChain({
        interactions: getOnChainInteractions(),
        threshold: 5, // minimum interactions
    });
    
    // 4. Publish attestations
    await network.publishBatch([
        ...eventAttestations,
        ...projectAttestations,
        ...onChainAttestations,
    ]);
}

Consuming Identity Data

// For applications
class IdentityConsumer {
    constructor(
        private network: IdentityNetwork,
        private requirements: TrustRequirements,
    ) {}
    
    async verifyUser(userId: string): Promise<VerificationResult> {
        // 1. Calculate trust from your perspective
        const trust = await this.network.calculateTrust(
            this.identity,
            userId,
            this.requirements.claimTypes,
        );
        
        // 2. Check Sybil resistance
        const sybilScore = await this.network.getSybilScore(userId);
        
        // 3. Verify specific claims if needed
        const claims = await this.network.getAttestations(
            userId,
            this.requirements.requiredClaims,
        );
        
        return {
            trusted: trust.value > this.requirements.minTrust,
            sybilRisk: sybilScore.risk,
            verifiedClaims: claims,
        };
    }
}

Conclusion

BFT-CRDT identity networks solve the fundamental paradox of decentralized identity:

No Central Authority: Trust emerges from the network
Sybil Resistant: Graph analysis detects fake identities
Privacy Preserving: Selective disclosure and ZK proofs
Contextual: Different apps interpret trust differently
Organic Growth: Builds on natural human relationships

This enables:

Truly decentralized social networks
Reputation-based lending without credit scores
Skills marketplaces without centralized platforms
Democratic governance beyond token-voting
Social recovery that actually works

The key insight: Identity is not a binary state but a graph of relationships that can be interpreted contextually while remaining resistant to attacks.

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