Zero Trust Engineering — Data-centric enforcement service architecture

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Data and information protection engineering reference for data-centric enforcement service architecture, including policy, logical interfaces, recovery and assurance.

Purpose: Data-centric enforcement service architecture. Domain: Data and information protection. Family: exchange. Scenario trigger: Invoke independent information policy enforcement. Input assurance: Information tags, identity assertions and requested transformation. Evaluation: Validate rights and obligations across resource handling paths. Governing policy: Data-centric protection and enforcement distribution policy. Resource-side obligation: Apply consistent access controls at every information gateway. Protected concern: Enterprise information APIs and content repositories. Logical interface: Data object tag policy grant enforcement hop and audit. Evidence: Policy decision enforcement point and obligation trail. Failure: Unsupported enforcement location or stale policy binding. Required recovery: Block unprotected channel and reconcile required enforcement. Architectural invariant: Information policy must remain effective independently of application location 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 · 29 elements · 34 relationships · validated on publish