Visualizing Data Security with AI/ML-Powered Data Classification

Abstract

Data Protection is an integral part of cybersecurity. With enormous amounts of data being produced, transferred, and consumed every day, securing an
organization’s sensitive data from leaking to the external internet is one of the challenges companies and cybersecurity professionals deal with every day. We found that the existing policy and criteria-based approach in cybersecurity software to identify anomalous activities limits the visibility, makes security administrators’ jobs time-consuming and ultimately leads to weakened data security. In this paper, we investigate how cybersecurity professionals can solve this problem with the power of AI/ML and we propose a more intuitive, novel dashboard and drill-down interface solution to make the sensitive data classification, organization, visibility, synthesis, and finally remediation efficient for security administrators.