EDRM Unveils Privacy Risk Reduction Model

Global News

24
Sep
2013

Editor

Model offers a process for cutting the volume of sensitive data for e-discovery

EDRM, the leading standards organization for the e-discovery market, announces the introduction of its new Privacy Risk Reduction Model. Developed by EDRM’s Data Set group, the model is a process for reducing the volume of private, protected and risky data by using a series of steps applied in sequence as part of the information management, identification, preservation and collection phases of the Electronic Discovery Reference Model.

The new Privacy Risk Reduction Model is used prior to producing or exporting data containing risky information such as privileged or proprietary information. It begins by defining risk and then identifying available data. The next steps involve creating and running filters before verifying output. These middle steps are cyclical and are repeated until the amount of private material is reduced to a desirable amount. The private data is finally quarantined in the final step before the remaining information is produced.

The EDRM Data Set Project provides industry-standard reference data sets of electronically stored information (ESI) and software files that can be used to test various aspects of e-discovery software and services. The group set out to develop the new Privacy Risk Reduction Model as a way to address ongoing concerns regarding the highly sensitive data often involved in the discovery process. Michael Lappin, director of archiving strategy at Nuix, and Eric Robi, president of Elluma Discovery, serve as the EDRM Data Set project co-leaders and, with key input from other group members, have been instrumental in creating the Privacy Risk Reduction Model.