Information security system based on multidimensional disparate user data

Abstract

Aspects of the disclosure relate to information security by identifying unique or related factors in common between individuals subject to a common threat vector. Data mining and data acquisition of public and non-public user information is performed to prevent, disrupt, and/or address criminal, cyber, and fraudulent threats. The information can be normalized into template(s) to align information across disparate datasets and enable efficient storage of the big data into appropriate fields to be tracked. The information can be stored in data warehouse(s) or in multidimensional data structure(s) for investigation if a threat vector against a group of individuals is detected. The multidimensional data can be analyzed to identify direct connections, common connecting entities, and/or connectivity clusters between individuals who were attacked or who may be attacked in the future. Remediation, machine learning, enhanced security, and/or vulnerability assessments may be implemented based on the results of the analysis.