Information Assurance for Real-Time Decision Support

Information is an important element in all decision making processes. Also, the quality of information has to be assured in order to support proper decision making in critical systems. In this paper, we present a comprehensive solution to information assurance. First we develop an ontology of information quality metrics, which can be used in assessment as well as in guiding the information processing procedures. To achieve proper information quality assessment, it is necessary to track the information flow as well as detect anomalous information processing flaws. We leverage existing data provenance and anomaly detection technologies and improve them to achieve real-time information quality assessment and problem detection.