Security and Privacy for Data Lakes

Deep Sensitive Data Discovery and Classification 

Privacera connects and scans files, tables across big data, cloud and traditional database environments. Privacera discovery engine can look at metadata, content, context and apply machine learning algorithms to accurately discover, classify/tag personal data (PII, PCI, PHI), restricted or confidential data. Privacera has inbuilt rules for across industries and geographies

Classification based data access control

Once the data is discovered, Privacera can help manage access to sensitive data. Access control is first step towards security and privacy, and ensures the data is accessible only on a need to know basis. Privacera leverages open sources plugins from Apache Ranger and Apache Sentry to enforce field, column and row level access control across Hadoop, Spark, AWS and other environments

Format preserving encryption and masking

The best form of data protection is anonymization of sensitive data. While masking and other practices have been in existence for long time, the challenge with masking that it renders the data unusable for analytics in big data and downstream systems. Privacera provides tools to do format preserving encryption (FPE), alphanumeric encryption, tokenization, masking and other techniques to enable enterprise adapt anonymization to their business needs. Privacera can anonymize data in Apache Kafka, Ni-Fi or any other ETL tools and can help users deanonymize data, based on a policy, in Hadoop, Hive, Spark or any application using APIs

Automated data access monitoring

As big data use grows internally in organizations, it is becoming challenging for governance and security teams to get accurate visibility on sensitive data and how its is moved and used across different applications. Privacera provides automated monitoring solutions for analyzing access history, other sets of information and creating alerts if data is accessed inappropriately or moved out of restricted data zones.

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