KBSI's Adaptive Toolkit for the Discovery of Threats (ATDT) project is developing 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 facilitates the automated generation of information from disparate and distributed data including news feeds, web databases, traffic reports, radio intercepts, human intelligence, etc. ATDT mines the data to extract meaningful knowledge or "indicators" of emerging threats. In addition, the toolkit's learning mechanisms adapt to changing data patterns, making threat detection and response increasingly timely, proactive, and comprehensive as the data set enlarges.

In Phase II of the project, KBSI is developing the ATDT Toolkit (ATDTT), a library of embeddable data mining component software tools that combines knowledge discovery methods with classical rule based techniques in an innovative architecture. This design makes the toolkit easily extendible and reconfigurable, allowing users to plug ATDTT into their favorite products and systems and apply techniques and technologies that were previously the coin of data mining experts. More advanced users can take advantage of ATDTT's solid framework to build custom data mining applications.

ATDTT has a wide range of applications beyond terrorist threat prediction, including emergency response management, target/decoy recognition and discrimination, industrial espionage detection, financial fraud detection, and computer network intrusion detection. The toolkit is also applicable for commercial industries with a need for knowledge discovery including the aerospace, automotive, shipbuilding, and construction industries. ATDTT can also be applied by corporations like internet marketing firms who are interested in Business Intelligence.