Identity document detection with convolutional neural networks for data loss prevention

Abstract

An identity document detector comprising a two-dimensional convolutional neural network is trained to detect categories of identity documents based on inputting unprocessed image data from documents. The documents comprise documents monitored by a data loss prevention (DLP) system across an organization, and each category of identity documents has associated risk levels for DLP. The DLP system performs corrective action to prevent data leakage based on detection of identity documents by the trained identity document detector and risk associated with the detected identity document categories as well as document context within the organization.

CPC Classifications