Semantic Access Control List (Semantic ACL)

Permissions are mapped to semantic categories rather than object IDs. An ACL rule might grant access to 'Q3 Financials' or 'PII' regardless of where the embedding resides in the vector space.

• Dynamic Association: New data is automatically protected based on its meaning.
• Policy Example: GRANT READ ON CATEGORY 'intellectual_property' TO GROUP 'legal_team'

Access is denied if the semantic similarity score falls below a defined confidence boundary. This prevents low-relevance data leakage where an attacker might retrieve loosely related sensitive information.

• Mechanism: A cosine similarity floor (e.g., < 0.75) triggers an automatic block.
• Benefit: Eliminates the risk of returning 'close enough' confidential data to unauthorized queries.

A protective proxy inspects and sanitizes both vector queries and responses. It analyzes the intent of the query to block adversarial prompts designed to extract data through indirect semantic associations.

• Inbound Defense: Detects malicious input vectors attempting model inversion.
• Outbound Sanitization: Prunes unauthorized results from the Top-K candidates before returning them to the user.

Combines semantic understanding with strict Boolean metadata filters. A user must satisfy both the conceptual permission (e.g., 'Project Atlas') and the static attribute check (e.g., clearance_level=5) to retrieve a vector.

• Dense-Sparse Reconciliation: Unifies permission models for semantic matches and exact keyword matches.
• Zero-Trust Posture: Never relies on semantic context alone; always validates explicit attributes.

Logically or physically partitions vector indexes to ensure strict data isolation between business units. A Semantic ACL enforces that a query from Tenant A can never traverse embeddings in Tenant B's namespace.

• Namespace Isolation: Groups collections into isolated workspaces.
• Architecture: Prevents cross-tenant semantic drift and unauthorized inference.

Embeddings are calibrated with mathematical noise to provide a provable guarantee against source data reconstruction. The Semantic ACL can enforce that only privacy-preserving vectors are served to lower-trust roles.

• Mechanism: Adds calibrated noise to the embedding before indexing.
• Utility Preservation: Allows high-level semantic analysis while preventing extraction attacks on individual records.