Introduction to privacy preserving synthetic data
1 like131 views
The document discusses privacy-preserving synthetic data generated for training AI and machine learning models, emphasizing the balance between data utility and privacy protection in a post-GDPR landscape. It outlines the concept of differential privacy and the importance of preserving statistical properties while enabling data processing. Additionally, it highlights the compliance benefits of using synthetic data in big data analysis and machine learning algorithms.
Related topics:1 of 12
More Related Content
What's hot (18)
Ad
Similar to Introduction to privacy preserving synthetic data (20)
Ad
Recently uploaded (20)
Introduction to privacy preserving synthetic data
- 3. the training of AI/ML models. self-driving vehicles,
- 4. 4 make information available for processing customer data in a post-GDPR
- 5. balance must be met between utility and the level of privacy protection Data privacy Data utility Ideal situation Acceptable trade-off
- 6. maximize the utility preserve to a high degree the statistical properties privacy-preserving synthetic data differential privacy
- 7. statistical information data structure No information
- 10. Big data analysis Training of machine learning algorithms: Cloud processing: Internal or external data sharing
- 11. speed agility Unlock any use Future-proof the compliance Benefits of privacy-preserving synthetic data
- 12. Find out more on www.statice.ai