Features - Anonymization | Kodex


Do you want to analyze personal data but are worried about security or regulatory compliance? Kodex can anonymize your data in real‑time while preserving most of its utility and structure. You can then use the anonymous data for data science, analytics or machine learning while ensuring compliance and protecting the privacy of your users or customers.

Anonymize all your structured data

Kodex can anonymize almost any kind of structured data. You can protect data from CSV files, databases (Postgres, MySQL, MSSQL, Oracle, ...), message queues (RabbitMQ, Kafka) or external APIs.

Batch and stream processing

Kodex can anonymize entire datasets in a single operation, or continunously read from data streams and produce anonymous data in real-time using time-window based aggregation.

Strong privacy model

Kodex uses three independent privacy mechanisms (cryptographic transformation, aggregation and randomization) to protect your data. The result is differentially private data with strong information-theoretic anonymity guarantees.

Structure-preserving method

Apart from an unavoidable utility loss due to the anonymization, Kodex largely preserves the probability structure of your original data. This enables you to perform explorative and predictive analysis on the anonymized data.

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This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 855978.