Data Sovereignty¶

Overview¶

Data sovereignty in AIDDDMAP ensures that data owners maintain complete control over their data throughout its lifecycle. This includes control over storage, access, processing, and monetization, while ensuring compliance with regulatory requirements and privacy standards.

Core Principles¶

1. Data Ownership¶

Clear definition of data ownership
Immutable proof of ownership
Transferable rights management
Granular control over data usage

2. Access Control¶

Role-based access management
Temporal access restrictions
Purpose-based limitations
Revocable permissions

3. Privacy Preservation¶

End-to-end encryption
Zero-knowledge proofs
Homomorphic encryption
Secure multi-party computation

Implementation¶

1. Ownership Management¶

interface DataOwnership {
  dataId: string;
  ownerId: string;
  created: number;
  proofs: OwnershipProof[];
  rights: DataRights[];
  history: OwnershipTransfer[];
}

interface OwnershipProof {
  type: ProofType;
  proof: string;
  timestamp: number;
  verifier: string;
}

interface DataRights {
  right: string;
  grantedTo: string;
  restrictions: AccessRestriction[];
  expiration?: number;
}

2. Access Control System¶

interface AccessPolicy {
  dataId: string;
  rules: AccessRule[];
  defaultAction: "allow" | "deny";
  version: number;
}

interface AccessRule {
  id: string;
  condition: {
    type: "role" | "time" | "location" | "purpose";
    value: any;
  };
  effect: "allow" | "deny";
  priority: number;
}

3. Privacy Controls¶

interface PrivacySettings {
  dataId: string;
  encryption: EncryptionConfig;
  proofs: ProofRequirement[];
  computation: ComputationPolicy;
}

interface EncryptionConfig {
  scheme: "AES" | "FHE" | "hybrid";
  keyManagement: KeyManagementPolicy;
  requirements: SecurityRequirement[];
}

interface ProofRequirement {
  type: "ownership" | "access" | "computation";
  scheme: "zk-snark" | "zk-stark";
  parameters: any;
}

Data Lifecycle Management¶

1. Data Ingestion¶

interface DataIngestion {
  source: DataSource;
  validation: ValidationRule[];
  preprocessing: ProcessingStep[];
  ownership: OwnershipAssignment;
}

interface ValidationRule {
  type: "format" | "quality" | "completeness";
  criteria: any;
  action: "accept" | "reject" | "transform";
}

2. Data Processing¶

interface ProcessingPolicy {
  allowedOperations: string[];
  restrictions: ProcessingRestriction[];
  auditRequirements: AuditConfig;
}

interface ProcessingRestriction {
  operation: string;
  conditions: {
    location?: string[];
    roles?: string[];
    purpose?: string[];
  };
}

interface SharingAgreement {
  parties: string[];
  purpose: string;
  duration: number;
  restrictions: SharingRestriction[];
  compensation?: CompensationTerms;
}

interface SharingRestriction {
  type: "usage" | "storage" | "transfer";
  condition: any;
  enforcement: EnforcementMethod;
}

Compliance and Audit¶

1. Regulatory Compliance¶

interface CompliancePolicy {
  regulations: string[];
  requirements: ComplianceRequirement[];
  validations: ComplianceCheck[];
}

interface ComplianceRequirement {
  regulation: string;
  controls: Control[];
  documentation: DocumentationRequirement[];
}

2. Audit Trail¶

interface AuditRecord {
  timestamp: number;
  action: DataAction;
  actor: string;
  resource: string;
  result: ActionResult;
  metadata: {
    location: string;
    purpose: string;
    authorization: string;
  };
}

interface ActionResult {
  success: boolean;
  details: string;
  compliance: ComplianceStatus[];
}

Integration Examples¶

1. Data Marketplace Integration¶

// Configure data listing with sovereignty controls
const dataListing = new MarketplaceListing({
  data: {
    id: "dataset-123",
    description: "Sensor Data 2024",
    preview: previewMetadata,
  },
  sovereignty: {
    ownership: {
      proof: ownershipProof,
      transferTerms: {
        allowedUsage: ["analysis", "model-training"],
        restrictions: ["no-resale", "eu-only"],
      },
    },
    access: {
      method: "fhe",
      proofs: ["zk-ownership", "zk-purpose"],
      duration: "30d",
    },
  },
  pricing: {
    model: "usage-based",
    rates: {
      query: 0.001,
      download: 0.01,
    },
  },
});

2. Compliance Workflow¶

// Configure compliance checks
const complianceWorkflow = new ComplianceChecker({
  data: dataset,
  regulations: ["GDPR", "CCPA"],
  checks: [
    {
      type: "data-retention",
      parameters: {
        maxDuration: "30d",
        sensitiveFields: ["pii", "financial"],
      },
    },
    {
      type: "access-control",
      parameters: {
        requiredRoles: ["data-processor"],
        geoRestrictions: ["EU"],
      },
    },
    {
      type: "encryption",
      parameters: {
        minStrength: 256,
        algorithms: ["AES-GCM", "ChaCha20"],
      },
    },
  ],
});

Best Practices¶

1. Data Management¶

Implement clear ownership tracking
Use strong encryption
Maintain detailed audit logs
Regular compliance checks

2. Access Controls¶

Principle of least privilege
Regular permission reviews
Strong authentication
Automated compliance checks

3. Privacy¶

Privacy by design
Regular privacy assessments
Data minimization
Purpose limitation

Future Enhancements¶

Planned Features
Enhanced compliance automation
Advanced privacy controls
Improved audit capabilities
Better integration options
Research Areas
Privacy-preserving computation
Decentralized identity
Automated compliance
Cross-border data flows

1. Resource Distribution¶

Implement proper limits
Monitor usage patterns
Handle resource conflicts
Regular optimization