How NER Finds Sensitive Data Hidden in Documents #shorts

Sensitive data detection was much easier when information lived inside structured databases. Tables, columns, field names, and predictable data types gave security teams a clear map of where sensitive information lived.

But when sensitive data moved into documents and PDFs, that map disappeared. Names, addresses, phone numbers, credit card numbers, and other sensitive information could be buried inside natural language.

That's where Named Entity Recognition (NER) became important. NER models can read documents and identify entities such as people, organizations, locations, phone numbers, addresses, and account-like patterns—helping security teams detect and protect sensitive data in unstructured documents.

This is how sensitive data detection evolved from column-level classification to document-level intelligence.

Topics covered: Sensitive Data Detection, NER, Named Entity Recognition, Data Masking, Document Security, PII Detection, AI Data Security, Data Privacy, Enterprise AI Security.

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#SensitiveData #NER #DataSecurity #AISecurity #dataprivacy