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Implement data anonymization pipeline for analytics exports #614

Description

@Smartdevs17

Context

Analytics exports contain PII (email, name, IP address) which violates data protection regulations when exported for third-party analysis or data sharing.

Current Limitation/Problem

Exports include raw user data. No anonymization or pseudonymization options exist before download.

Expected Outcome

Configurable data anonymization pipeline: strategies (mask, hash, truncate, perturb) applied per field before export, with irreversible anonymization for GDPR-compliant exports.

Acceptance Criteria

  • Anonymization strategies: email mask (j***@example.com), name hash (SHA-256 + per-export salt), IP truncation (192.168..), date perturbation (+-3 days uniform)
  • Configurable per export type: full (admin only), pseudonymized (analytics team), anonymized (third-party)
  • Irreversible guarantee: anonymized exports include no reversible mappings or encryption keys
  • Export audit log: record anonymization level, fields transformed, timestamp, requester
  • Preview: show anonymized sample rows before export download
  • k-anonymity check: warn if fewer than 5 records share identical quasi-identifiers
  • Edge case: small dataset (<20 records) -> warn user of re-identification risk before export

Technical Scope

  • backend/analytics/domain/anonymization/ - AnonymizationPipeline orchestrator
  • backend/analytics/domain/anonymization/ - strategy implementations (MaskStrategy, HashStrategy, TruncateStrategy, PerturbStrategy)
  • backend/analytics/controller/ - anonymization configuration API
  • backend/analytics/tests/ - k-anonymity validation and re-identification risk tests
  • backend/gdpr/ - data classification registry (PII field annotations)

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200-points200 point issueStellar WaveIssues in the Stellar wave programdrips-waveIssues in the Drips Wave programhighHigh complexity issue

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