Passive AI Output Obfuscation - AI Mitigation

Obfuscating model outputs reduces an adversary's ability to create effective adversarial inputs.

Obfuscating model outputs reduces an adversary's ability to generate effective adversarial data.

Obfuscating model outputs can reduce an adversary's ability to produce an accurate proxy model.

Suggested approaches:

• Restrict the number of results shown
• Limit specificity of output class ontology
• Use randomized smoothing techniques
• Reduce the precision of numerical outputs

Suggested approaches:

• Restrict the number of results shown
• Limit specificity of output class ontology
• Use randomized smoothing techniques
• Reduce the precision of numerical outputs

Obfuscating model outputs can prevent adversaries from collecting sensitive information about the model outputs.

Suggested approaches:

• Restrict the number of results shown
• Limit specificity of output class ontology
• Use randomized smoothing techniques
• Reduce the precision of numerical outputs

Suggested approaches:

• Restrict the number of results shown
• Limit specificity of output class ontology
• Use randomized smoothing techniques
• Reduce the precision of numerical outputs

Suggested approaches:

• Restrict the number of results shown
• Limit specificity of output class ontology
• Use randomized smoothing techniques
• Reduce the precision of numerical outputs

Obfuscating model outputs restricts an adversary's ability to create an accurate proxy model by querying a model and observing its outputs.

Obfuscating model outputs reduces an adversary's ability to verify the efficacy of an attack.