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Page créée avec « * Standardize the anonymization of data collection, storage and transmission encryption. * Implement information leak detection scenarios for the entire data pipeline * Provide a specific, isolated training environment with restricted access to libraries for those handling the data sets. * Regularly validate the security level of open-source libraries and components used in training and validation environments. * Build adversarial datasets with identified risk sc... » |
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Dernière version du 5 décembre 2023 à 15:38
- Standardize the anonymization of data collection, storage and transmission encryption.
- Implement information leak detection scenarios for the entire data pipeline
- Provide a specific, isolated training environment with restricted access to libraries for those handling the data sets.
- Regularly validate the security level of open-source libraries and components used in training and validation environments.
- Build adversarial datasets with identified risk scenarios to validate model changes
- Launch models in production in secure enclaves with limited execution rights.
- Monitor systems for deviations
