Cloud Computing Disaster Recovery

Quest Technology Management

Helping clients manage their technology for over 30 years.

How DLP solutions identify sensitive data

Data identification relies on a DLP analysis engine that conducts deep content analysis based on central policies. Among the techniques used: Partial document matching and database fingerprinting (or exact data matching) as well as rules-based, conceptual, statistical, predefined categories (like PCI compliance), and various combinations of these. In addition, some DLP analysis engines also implement vector machine learning techniques. The stronger the analysis engine, the more accurate is its data identification, which is a key factor in limiting both false positives and false negatives — so DLP deployments should be tested for accuracy and both they and the policies they enforce should be tuned to ensure minimal false positives/negatives.

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