Anonymization & Masking

Run Analytics on Your Data While Preserving Privacy

Privacera’s anonymization and masking capabilities de-identifies any personal or sensitive information by replacing it with non sensitive data that maintains the original data’s analytical value, resulting in continuous privacy and compliance without disrupting the use of data.

Why De-Identify Data?

Faced with rigorous privacy and compliance mandates, enterprises are looking to de-identify sensitive information before storing and analyzing it in the cloud but without impacting the data’s usefulness.

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Privacera enables various forms of anonymization to ensure data protection and preserve privacy while maintaining the referential integrity and analytical value of the data.

Simplify Data Protection and Privacy Compliance at Scale

Enable Data for Analytical Use

Safely analyze all your data, including sensitive data such as personally identifiable data (PII), while preserving customer privacy.

Control Access to De-Identified Data

Privacera enables centralized policies to control which users can re-identify data. Privacera provides UDFs and APIs to enable seamless re-identification on demand.

Achieve Compliance

Meet stringent compliance, privacy, and regulatory requirements including GDPR, CCPA, PCI, HIPAA, and PII mandates.

Why Privacera Anonymization?

Preserve Analytical Insights and Privacy

Privacera anonymization preserves the referential and statistical integrity of data when it is anonymized. Use data for analytics and machine learning while compliance and privacy is maintained, even if the data is copied.

Built for the Cloud

Privacera anonymization is deeply integrated with ETL and data consumption tools, and can provide performance-efficient enforcement across cloud datastores and databases. Privacera anonymization can run as a microservice and integrates into DevOps workflows.

Centralized Key Management and Policies

Privacera leverages Apache Ranger’s key management to store keys and enable fine-grained access control policies at the user or group level. Privacera key management is also integrated with popular cloud key vaults.

Frequently Asked Questions

What is the difference between field encryption and masking?

Encryption uses keys and algorithms to create random pseudo characters for a given value. Encrypted values can be reversed with the key and by applying a decryption algorithm. Encryption can be used when data needs to be protected at rest and in use, while enabling certain users to reverse the encryption and get the original data back. Masking data is typically one-way and not reversible. Masking can be used to remove PII data altogether.

Can data be anonymized as part of data ingestion?

Privacera integrates seamlessly with Apache Kafka, Apache NiFi, and StreamSets and can anonymize data as it is being ingested.

Can the encryption keys be stored in an external key store?

Privacera can store keys in external HSM or cloud-based key vaults.

Resources & Latest News

Whitepaper

Security and Privacy for Modern Data Platforms

Learn how to enable comprehensive security, privacy and governance in big data and cloud environments using Privacera.

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Privacera for Amazon EMR

Use this link to request a Docker package to install fine-grained access control to Amazon EMR.

Interested in Seeing Anonymization in Action?