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The leakage, or extrusion, of privacy-sensitive personal information has been shown to have significant negative consequences on an organization’s brand, reputation, and customer trust as well as legal, operational, and financial implications.

With the number of extrusions of personal information on the rise, both governments and industry organizations have responded by instituting several privacy laws and industry operating standards with which all organizations must comply. To satisfy the increasing number of legislation and industry regulations designed to protect the personal information of consumers, employees, and private citizens, organizations must be able to detect identity information in outbound network traffic and prevent its unapproved distribution. This privacy sensitive information can be referred to a variety of ways, the most common of which is personally identifiable information (PII).

For organizations to protect PII they must put policies and tools, such as a data leakage prevention solution, in place to monitor and control privacy-sensitive identity information. Content recognition is a key component to any such solution. Content recognition is the process of applying algorithms to examine material for a match to a particular type of information. A variety of content recognition methods exist, though most methods fall into two general categories—profiling and registration.

  • Profiling of data uses rules that describe information, typically statistical, pattern and/or key attributes that the system uses to evaluate information. It does not require that the actual protected information be provided.
  • Registration of data requires that protected content be enrolled in the system. This system then generates algorithms to detect an exact match or fingerprint of the actual content that has been registered with the system.

There are two key criteria when evaluating content recognition capabilities of a data leakage or extrusion prevention solution:  Accuracy and management.


The ability to accurately recognize protected content, identity information in this case, is measured in the number of false positives and false negatives.


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