Machine learning techniques for mitigating aggregate exposure of identifying information

Abstract

Systems and methods mitigate aggregate exposure of identifying information using machine learning. A privacy monitoring system identifies entities and corresponding entity types by applying a set of domain-specific neural networks, each trained to recognize a particular entity type, to media data extracted from two or more content items associated with a user. The privacy monitoring system computes a privacy score indicating a cumulative privacy risk for potential exposure of identifying information associated with the user from the two or more content items by identifying connections between the identified entities. The connections between the entities are weighted according to the entity types and contribute to the privacy score. A reporting subsystem outputs an indication of a recommended action for mitigating the cumulative privacy risk.