Why classic anonymization (and pseudonymization) does not result in anonymous data
Why do classic anonymization techniques (Pseudonymization) offer a suboptimal combination between data-utlity and privacy protection?
Why do classic anonymization techniques (Pseudonymization) offer a suboptimal combination between data-utlity and privacy protection?
Our quality report containing various statistics from synthetic data generated through our Syntho Engine in comparison to the original data.
How Moquer embraces synthetic data to boost customer service, data driven innovation and privacy protection.
We challenged one commonly considered and, unfortunately, still frequently applied approach of data anonymization: removing names.
By using the Syntho Engine to anonymize datasets we can leverage the interesting properties of Machine Learning research datasets, without opening up the possibility for fraud.
As three friends and founders of Syntho, we believe that artificial intelligence (AI) and privacy should be allies, not enemies.
Have a look at the Syntho achievements. During the years we participated in various events from where we collected different awards.