Do you get too many "suspect" leads of insiders stealing patient medical data, stealing financial data or violating patient privacy? Veriphyr patent-pending clustering analytics avoids the false leads of static rules.
Veriphyr behavioral clustering analytics discern which access by employees and contractors is work related and which is done to steal patient data or violate patient privacy. Veriphyr detects the worker's actions early so the problem can be addressed before a patient becomes a victim.
Discovers Data Theft Hidden in an Employee's Legitimate Work Activity
Veriphyr uses only your existing logs from disparate applications and medical devices. The clustering analytics automatically discover self-similar groups of workers and patients based on their activity, not static rules or roles. Veriphyr then finds anomalous interactions of worker-customer that are actual data thefts or privacy violations based on the groupings.
Unified Detection of Data Theft Across All Applications
Veriphyr discovers patient data theft and privacy violations, not just in an Electronic Medical Records (EMR) system, but in any clinical and business applications containing Protected Health Information (PHI).
Veriphyr works with any system, any format, or any medical device containing PHI or patient financial data.
Complete Details on Workers and Patients
Veriphyr extracts patient and worker demographics directly from the disparate data dumps so the reports include department, job title, manager, address, and other relevant context.
No data needs to be hand input because Veriphyr automatically correlates user and patient identifiers across all applications to real workers and real patients in your HR, contractor, and patient databases.