Zero Trust Engineering — Data masking, tokenization and redaction

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Data and information protection engineering reference for data masking, tokenization and redaction, including policy, logical interfaces, recovery and assurance.

Purpose: Data masking, tokenization and redaction. Domain: Data and information protection. Family: decision. Scenario trigger: Serve constrained information projection to consumer. Input assurance: Field labels, permitted purpose and sensitivity obligations. Evaluation: Calculate permitted transformation for each field or value. Governing policy: Masking tokenization and irreversible redaction policy. Resource-side obligation: Return purpose-limited data representation and conceal originals. Protected concern: Privacy-sensitive enterprise response. Logical interface: Field class allowed transform token domain policy output and verification. Evidence: Transformation plan data lineage and output inspection audit. Failure: Incorrect masking rule or reversible disclosure in lower-trust context. Required recovery: Suppress response and rotate exposed token mapping. Architectural invariant: Transformations must preserve required utility without leaking prohibited data Adoption: replace reference roles with concrete owner-controlled services. Specify exact provider/consumer identities, schema fields and classifications, signal provenance and freshness, idempotency, authorization lifetime, timeout/retry limits, observation and tamper evidence. A denied or failed operation must not silently become a permitted one. Scope: original vendor-neutral, implementation-agnostic technical reference model. Illustrative logical components and behaviors are neither a deployed system nor evidence of regulatory compliance. Package identities remain stable within the package; cross-package semantic reconciliation requires separate explicit registry support.

Curated · other · unspecified · Published by Lattix · 28 elements · 34 relationships · validated on publish