Organisations increasingly recognise that data is their greatest asset. However, valuable datasets often contain sensitive information about individuals, so to comply with governance and regulation, responsible organisations restrict the distribution and reuse of this data, presenting significant barriers to innovation.
 

Privitar Lens is a privacy-preserving query interface well suited for reporting and statistical analysis.

Privitar Lens allows analysts to perform sophisticated analytical queries of the data (e.g. counts, sums, histograms), but prevents direct access to the underlying sensitive data.

Usage is subject to strict authentication and access control, and all queries are logged and audited. It allows data holders to post tables with their desired privacy controls for each analyst and for each column. Privacy controls are then dynamically applied to each query submitted.

Privitar Lens Key Features

Privitar Lens uses noise addition to prevent users from extracting private data, ensuring differential privacy. Further protection comes from behaviourial analytics for attack detection. 


Privitar Lens tracks each query and calculates the total privacy risk across queries. It stops releasing new results after the privacy risk reaches a pre-defined threshold.

Privitar Lens has a number of features which make the product easy to use for non-privacy experts, including an intuititive web interface and REST API. It connects to data stores such as PostgreSQL or Hive with an extensible set of connector modules. Privitar Lens is installed on-premise or in the cloud.

 

Creation of new data products


  • Controlled querying of sensitive data: enable safe access without disseminating the dataset

  • Create structured and dynamic data products

  • All queries are audited for complete visibility of data access

Interactive Analysis

 

  • Perform interactive analytics and data science without direct access to raw data

  • Execute custom code in a privacy-preserving sandbox

  • Conduct behavioural and threat modelling

Learn More or Request a Demo

 

 

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