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Closing the data privacy gap: Protecting sensitive data in
non-production environments
An IBM Optim White Paper
www.optimsolution.com
Abstract
This white paper explains why protecting sensitive information and ensuring privacy have become high priorities. News headlines about the increasing frequency of stolen information and identity theft have focused awareness on privacy breaches and their consequences. In responding to this issue, data privacy regulations have been enacted around the world. Although the specifics of these regulations may differ, failure to ensure data privacy compliance can result in millions of dollars in financial penalties and jail time. Companies also risk losing customer loyalty and destroying brand equity. The impact is serious enough to put a company out of business.
Companies rely on critical ERP, CRM and custom applications to support daily business operations, so it is essential to ensure privacy and protect application data no matter where it resides. However, the same methods that protect data in production environments may not meet the unique requirements for non-production (development, testing and training) environments. How can IT organizations protect sensitive data, including employee and customer information, as well as corporate confidential data and intellectual property? Industry analysts recommend "de-identifying" or masking data as a best practice for protecting privacy.But, what are some of the requirements for selecting a data privacy solution?
The ideal data privacy solution must provide the necessary data masking techniques to satisfy the simplest and most complex privacy requirements. These techniques must produce results that accurately mask context-sensitive data in a way that reflects the application logic and preserves the integrity of the data. The solution must also include a way to propagate masked data elements consistently across applications and operating environments to generate valid results.
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