Categorization of Discoverable Cyber Attributes for Identity Protection, Privacy, and Analytics

The Internet has become a major source of data that many regard as personally identifiable, and the ease of accessibility may be considered as an invasion of privacy. While there are certainly benign uses of this data, it has also facilitated increases in identity theft and identity fraud. This paper presents classes of cyber identity attributes that can aid in analysis and protection of a person's sensitive data in a complex, changing environment. Our research is motivated by the need to understand and organize identity attributes in such a way as to inform the general public of what Personally Identifiable Information (PII) is available and how it may be better protected. In this paper, we outline and discuss five major categories of identity attributes that are discoverable online. The categories discussed relate to data that is biographic, behavioral, relationship, biometric, and physiological data which are all part of a holistic representational model for identity analytics.