Which of the following approaches BEST enables the separation of sensitive and shareable data to prevent an AI chatbot from inadvertently disclosing confidential information?

The correct answer is C. Siloing. Siloing organizes data into distinct, isolated groups so that the AI chatbot's data access is restricted exclusively to the non-sensitive silo designated for it. Because sensitive data resides in a separate silo the chatbot cannot reach, inadvertent disclosure becomes…

AI Security Design and Implementation

Question

Options

AZero Trust
BSandboxing
CSiloing
DContainerization

How the community answered

(23 responses)

A
4% (1)
B
13% (3)
C
78% (18)
D
4% (1)

Explanation

Siloing organizes data into distinct, isolated groups so that the AI chatbot's data access is restricted exclusively to the non-sensitive silo designated for it. Because sensitive data resides in a separate silo the chatbot cannot reach, inadvertent disclosure becomes architecturally impossible. Zero Trust (A) is an identity and access control framework - it verifies every access request but does not inherently separate data by sensitivity for AI consumption. Sandboxing (B) isolates application processes or code execution environments but does not specifically partition data into sensitivity tiers. Containerization (D) packages application code and dependencies together but does not address logical data classification and separation.

Topics

#AI Data Security#Data Segregation#Confidentiality#Data Leak Prevention

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