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White Papers

Providing in-depth analysis, our White Papers enable the most informed decisions as you consider a data masking solution. Our transparent approach ensures the provision of a clear perspective, allowing you to objectively consider your data masking needs.

The Camouflage White Papers represent the most topical issues in data masking today.

Data Masking Best Practices

Four Phases of Evaluating and Implementing a Data Masking Solution
The over-riding factor in choosing data masking is for the protection of data privacy by de-identifying sensitive data in non-production environments. The prospect of Personally Identifiable Information (PII) falling into the wrong hands strikes fear among many data center managers. Data security remains the paramount criterion when deciding which data masking solution to choose. Your clients expect it. Industry standards require it. The law demands it.

This white paper provides an overview of the four phases of the Data Masking Lifecycle. This document will also review the data masking methodology, identifying key data masking milestones, an estimate of human capital required for data masking and the timeframe needed to implement and deploy data masking within a typical enterprise.

Data Masking: Strengthening Data Privacy and Security

Many business activities require access to real production data, but there are equally many that do not. Data masking secures enterprise data by eliminating sensitive information, while maintaining data realism and integrity. Many Fortune 500 companies have already integrated data masking into their PCI DSS and GLBA compliance programs, and so can you.

  • Learn how the latest advancements in data masking technology can be used to improve your compliance with PCI DSS and GLBA security requirements.
  • Learn how data masking generates secure, yet realistic, data that can be used to protect against theft in application development and testing.
  • Learn how data masking complements other technologies in your security program and how to select a data masking solution that fits your enterprise.
Secure Analytics - Maximizing Data Quality & Minimizing Risk for Banking and Insurance Firms

Does your organization use real customer profiles and statistics to drive marketing efforts or real employee data for salary/benefit analysis? Is your organization conducting one of these or other critical business activities that require data analysis? While these activities are critical to organizational success, they can put your organization at risk for a data breach. Camouflage Secure Analytics maintains the data’s original statistical properties, allowing for effective research, testing, and development while limiting the risk of disclosure of personally identifiable information. Give clearance for necessary business activities to proceed and rest assured that your sensitive data is protected.

  • Traditional security measures - firewalls, passwords, and encryption - are not enough to effectively protect against the threat of data breach.
  • Learn how an optimal data security solution will allow for effective usage of your organization’s data while protecting sensitive information and allowing you to operate in compliance with GLB and SOX.
  • See how Camouflage Secure Analytics uses data shuffling to de-identify data, while maintaining the statistical properties of the original data set.
Meet PCI DSS Compliance Requirements for Test Data with Data Masking

Whether you are working towards your first or next PCI DSS audit, you know that compliance isn’t scored as a one or a zero – it’s measured on a sliding scale. You’ve successfully argued for adoption of various security technologies to protect cardholder data, including encryption and firewalls, and have come to recognize that compliance cannot be achieved with one panacean policy or technology; each is part of a larger puzzle, which never quite looks right without all the pieces in place.

  • PCI DSS compliance can’t be achieved with just one policy or technology - each is part of the larger puzzle.
  • Using data masking, a technology which alters sensitive information while maintaining realism, production data can be eliminated from testing and development environments.