Identity Analytics And Belief Structures

Abstract

Personal identity is an important topic in information systems in general and data analytics in particular. Normally associated with digital security and privacy, the scope of identity is much greater and affects most aspects of everyday life. Related subjects are behavioral tracking, personal-identifiable information (PII), privacy data relevance, data repurposing, identity theft, and homeland security. The purpose of this paper is to establish a context for using analytics to combine evidence to categorize certain subjects based on belief structures.