Abstract: Disclosed are a method and computer system for quantifying identity risk associated with an agent's request for access to online resources using valid credentials of an authorized user. The likelihood that the agent is the authorized user is computed using access request data, historical access data for the authorized user, and identity risk signal data collected from open source intelligence (OSINT) and other external identity risk data sources. The likelihood may be based on the distance between the current digital fingerprint, which in an embodiment is a high-dimensional vector comprising identity risk signal data, and a similar historical digital fingerprint for the authorized user, or, alternatively, the deviation from mean between a current weighted risk score comprising the identity risk signal data and the historical weighted risk scores for the authorized use.

Abstract: Disclosed are a method and computer system for quantifying identity risk associated with an agent's request for access to online resources using valid credentials of an authorized user. The likelihood that the agent is the authorized user is computed using access request data, historical access data for the authorized user, and identity risk signal data collected from open source intelligence (OSINT) and other external identity risk data sources. The likelihood may be based on the distance between the current digital fingerprint, which in an embodiment is a high-dimensional vector comprising identity risk signal data, and a similar historical digital fingerprint for the authorized user, or, alternatively, the deviation from mean between a current weighted risk score comprising the identity risk signal data and the historical weighted risk scores for the authorized user.