Advanced Cyber Security & Threat Detection

The U.S. defense and intelligence communities are undergoing a revolution in operations, driven largely by network-centric technologies.  In today’s global environment, war fighters, analysts and decision makers are not only geographically dispersed but are also very likely to reside in multiple security domains.  There have been reports of serious compromises in United States Air Force, Army, and State Department networks by organizations and nation states that are openly hostile to the United States.  These examples show that determined and sophisticated adversaries can circumvent current computer network defense technologies and compromise DoD networks without fear of detection.  The national security implications of these cyber attacks are significant.  KBSI has leveraged its capabilities in semantic search and threat detection in developing a number of technologies that address these cyber security issues.

Conventional military threats--such as a missile command posts, an armored division, a naval task force, or an air wing--can be reliably detected by reconnaissance satellites and other technical collection assets. The costs for delivering this capability, however, is significant, and the technological sophistication of the detection systems make them time consuming to build. KBSI has extensive experience in developing innovative technologies for pattern discovery and monitoring that can be applied to a variety of threat detection arenas. These include:

a dashboard that provides automation support for 24/7 asymmetric threat assessment from open-source data;
an automated system for Deep Semantic Extraction (DSE); and
a system, currently in development, that is capable of using open-source data to identify and model networks of hostile activities. 

 

Adaptive Toolkit for the Discovery of Threats (ATDT)

KBSI developed a toolkit that integrates intelligent knowledge discovery techniques, advanced data mining technologies, and knowledge-based methods for automated threat detection. ATDT is an agent-based decision support system that mines data (news feeds, web databases, traffic reports, radio intercepts, human intelligence, etc.) to extract meaningful knowledge or "indicators" of emerging threats.

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Blood Reserve Availability Assessment, Tracking, and Management System (BRAMS™)

KBSI is developing a system that allows users to manually enter data via a Web-based system, and to apply data mining and analytics in detecting blood supply problems, analyzing system behavior, evaluating alternate solutions, and optimizing the blood supply chain.

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Information-Fusion based Indication & Warning Assessment and Recognition System (IIWARS)

KBSI developed a system that, using text mining technologies and information fusion, improves the DoD's terrorist threat assessment capabilities. IIWARS uses advanced text and data mining methods to mine data from multiple, distributed text sources (news feeds, web databases, traffic reports, radio intercepts, human intelligence) and extract multiple features and "indicators" of an emerging or actual threat. These indicators are then fused into a threat model which can be compared to hypothesized threat Course Of Action (COA) templates.

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Human Enemy Network Influence Operations Map (HEN-IO-MAP)

KBSI is researching and designing and demonstrating an advanced utility-theoretic preference model for influence operations (IO) modeling. The HEN-IO-MAP system will apply utility theoretic models in creating a human enemy network influence operations map that incorporates cultural, social, and other factors using a simple knowledge acquisition process. The system will assist influence operations (IO) planners in the evaluation and formulation of influence operations.

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