Results for "privacy attack"

A formal privacy framework ensuring outputs do not reveal much about any single individual’s data contribution.

Attacks that infer whether specific records were in training data, or reconstruct sensitive training examples.

Stepwise reasoning patterns that can improve multi-step tasks; often handled implicitly or summarized for safety/privacy.

Artificially created data used to train/test models; helpful for privacy and coverage, risky if unrealistic.

A discipline ensuring AI systems are fair, safe, transparent, privacy-preserving, and accountable throughout lifecycle.

Privacy risk analysis under GDPR-like laws.

Compromising AI systems via libraries, models, or datasets.