Fingerprinting

The Netskope Fingerprint capability offers robust, multi-modal data identification, extending beyond simple text analysis to comprehensively support both images and text data types. This advanced functionality allows organizations to accurately identify sensitive content across a wider range of file formats, ensuring that proprietary or regulated information in documents and visual assets is consistently protected.

To ensure efficient and accurate training of the fingerprint models, the platform provides sophisticated management tools for your training data. Users can manage their training data efficiently from the UI, streamlining the process of preparing and curating the content used to create unique digital fingerprints. A key feature is the support for bulk upload, which significantly accelerates the ingestion of large volumes of training data, making it quicker to establish robust fingerprinting rules across the organization. Furthermore, the system includes powerful features for quality control, specifically supporting exclusions to remove edge cases. This is crucial for refining the model’s accuracy, allowing administrators to filter out ambiguous, irrelevant, or specific non-sensitive documents that might otherwise introduce noise or false positives into the resulting fingerprints, thus maximizing the precision of the data loss prevention (DLP) policies.

• Groupes d'empreintes digitales
• Créer des règles d'empreintes digitales