Highlights
- On-the-fly table confidentiality.
- In-built routines for low-value cell disturbance or suppression.
- Consequential suppression available.
- Plug-in API for customizable confidentiality routines.
- Background statistics such as top contributors and frequency counts available for use in suppression routines.
- Table auditing facilities available.
- Pre- and post-tabulation rules can be applied.
- Permissions to allow privileged users the choice of generating raw data or confidentialized results.
Overview
Many government organizations need to disseminate statistical information derived from data gathered from individuals or businesses. It has become increasingly important to both government and business to prevent disclosure of the private details in that data (protecting privacy) while still providing appropriate access to the data and a means of effectively analyzing it.
The SuperSTAR software suite developed by Space-Time Research is unique for its sophisticated and extensible data confidentialization methods and options. SuperSTAR delivers on-the-fly confidentialization for ad hoc, user-defined cross tabulations of census and survey microdata.
The confidentialization methods the SuperSTAR suiteoffers include:
- cell disturbance via perturbation — as applied by the Australian Bureau of Statistics (ABS) with their groundbreaking CDATA Online and TableBuilder web applications
- cell disturbance using rounding techniques
- primary cell suppression
- secondary (consequential) cell suppression using SuperSTAR’s integration with Tau-ARGUS©
- business rules limiting the number of dimensions and hierarchical classification levels that can be included in across tabulation.
An organization can also implement its own special or nonstandard confidentialization methods as plugins to SuperSTAR’s Data Control API.
Secure Access
Only individuals who are verified as a user can view data to which they have been granted specific rights. Groups of users can be created that have similar permissions but are granted specific detailed data access. The groups can be associated to different data access profiles, which ensures a single, consistent repository of data serves all user groups in a secure and suitably controlled manner.
Disclosure Control Methods
There are a variety of methods used to protect data. In some cases, several methods are combined.
- Aggregation – the creation of summary tables or cubes.
- Confidentialization of microdata – sampling and/or perturbing values on data records so that an effectively anonymous set of records can be safely released.
- Confidentialization of tabular data – concealing or adjusting values in aggregate data before release.
- Business rules – controlling the level of detail in queries using pre‐defined rules.
- Trust and access control – providing more detailed access to trusted groups of users.
- Monitoring – recording and reviewing the types of queries executed by individual users and/or groups.
Read the Confidentiality Solution Paper to find out more about Disclose Control Methods and how the methods are implemented using the Data Control API.
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These methods reduce the amount of information that can be provided to users and each method has a unique set of benefits and limitations. The three most important points to be considered when designing Dissemination Solution involving these methods are:
- Computational complexity, cost, and timeliness.
- Additivity, consistency, and accuracy of subsequent derivations.
- Consequential confidentiality.
Read the Privacy Protection - Disclosure Control and Confidentiality White Paper to find out more about Disclose Control Methods, their target audience, and the benefits and limitations of each method.
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Dissemination Solutions and Confidentiality
When planning to disseminate statistical information on the Web an organization needs to consider the target audience. The choice of disclosure control method(s) depends on the kind of application used for dissemination as well as the audience.
Given the increasing demand for access to information resources via the Web and the substantial cost advantage of providing end users with self‐service facilities; more organizations are exploring the possibilities of ‘on‐demand’ confidentialization and privacy protection. In an ideal world, robust, automated disclosure control methods would be applied dynamically as information requests were generated from a web‐based, self‐service interface.
Read the Privacy Protection - Disclosure Control and Confidentiality White Paper to find out more about what Disclosure Control Method is right for the target audience.
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Contact us
To find out how our solutions meet your requirements, please contact us.