Information Trustworthiness, Integrity Non-Language Speech

Securboration, working with Dartmouth University researcher Dr. Eugene Santos Jr., proposes the Semantic Integration Environment for Determining Information Trustworthiness (SIEDIT). The key barriers to effective information utilization is that analysts either use information with no underlying knowledge of its pedigree, or they disregard information in its entirety due to a lack of confidence in the data. SIEDIT will provide a formal basis for processing and validating incoming net-centric data to standardize information and verify information trustworthiness and integrity in a distributed computing environment such as the Air and Space Operations Center (AOC). Securboration’s innovation is to employ a unique combination of models and technologies to standardize, weigh, and present information to the user to significantly improve the user’s access to the right data and confidence in that information. User’s can perform tasks more efficiently because they will focus on the data that matters most. SIEDIT uses a powerful Analytic Hierarchy Process (AHP) matrix algorithm that allows the user to rank the importance of structured and unstructured datatypes with respect to a specific task or situation. This information, along with quality and confidence metadata, is fed to a SIEDIT-created Bayesian Knowledge Base (BKB) that assesses data integrity and trustworthiness in real-time.