Adaptive Toolkit for the Discovery of Threats
The ATDT toolkit integrates intelligent knowledge discovery techniques, advanced data mining technologies, and knowledge-based methods for automated threat detection. The tool provides agent-based decision support by mining data to extract knowledge or "indicators" of emerging threats.
While analysts and strategists are well versed in tracking threats to conventional military targets, the new asymmetric threats posed by terrorist organizations--as 9-11 has made devastatingly clear--are much more difficult to anticipate. Threats to military targets have traditionally required capabilities that are both expensive and time consuming to develop--activities that satellites and other reconnaissance technology and techniques are more likely to notice. Asymmetric terrorists threats, on the other hand, are generally smaller in operation, can be mounted much more quickly, and require significantly less financial investment. This lighter trail makes such threats extremely difficult for traditional intelligence gathering methods to detect, but no less important: a study by the Defense Science Board Study on Transnational Threats found that "the making of connections between otherwise meaningless bits of information is at the core of (transnational) threat analysis."
KBSI's Adaptive Toolkit for the Discovery of Threats (ATDT) initiative 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 facilitates the automated generation of information from disparate and distributed data that includes 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 even as the data set enlarges.
Phase II Development
In Phase II of the initiative, KBSI developed 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 whose that were previously limited to use by data mining experts. More advanced users can, however, 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 that have a need for knowledge discovery, including the aerospace, automotive, shipbuilding, and construction industries. ATDTT can also be applied by corporations—internet marketing firms, for example—that are interested in Business Intelligence.
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