Innovative Data Authentication Model

Big data based user authentication is a new approach that leverages the power of the Big Data analytics to develop a fertile field for the next generation authentication protocols. This new approach relies on “something you do”-based verification methods, where the users' dynamic behaviors are analyzed in order to generate real-time uniquely identifiable information about them. Once the unique user's identification is generated “authentication on demand” can be achieved through user challenging questions that are dynamic and user specific. In this paper, the 3Vs nature of Big Data (volume, variety and velocity) is utilized to propose an Innovative Data Authentication Model (IDA). IDA model is a new implementation for the Big Data based user authentication in finding out unique patterns of the users' dynamic behaviors to be used as a basis for the user challenging questions generation process. In other words, Big Data analytic techniques such as association learning and behavioral classification will be used to compile the human dynamics into flexible security user profiles. The term “human dynamics” comprises the actions of human and their impacts on behavioral outcomes. The real-time analysis of these users' profiles helps generate a random set of challenging questions thereby “authentication on demand” feature is obtained. A practical use case scenario has been given to illustrate how IDA works from creating user profiles, to studying and classifying human dynamics and generating questionnaire with security potentials to authenticate users.