CEDAR (Complex Event Discovery, Analysis, and Ranking) Navy STTR FY2010.A Sol No.: Navy STTR FY2010.A Topic No.: N10A-T040 Topic Title: CEDAR (Complex Event Discovery, Analysis, and Ranking) Proposal No.: N10A-040-0061 Firm: 21st Century Technologies Inc. 6011 West Courtyard Drive Bldg 5, Suite 300 Austin, Texas 78730 Contact: Chris Augeri Phone: (512) 342-0010 Web Site: www.21technologies.com Abstract: 21CT and CUBRC propose CEDAR (Complex Event Discovery, Analysis, and Ranking), a robust framework to detect and analyze indicators of complex activities, such as an insurgent ambush observable via myriad of simple events in multiple sensor streams. CEDAR will provide a mapping from complex behavior, such as conducting an insurgent ambush or rebuilding trust in local communities, to simple event indicators detectable in intelligence, open-source, blue force, and population sensor streams. Examples of such events include increased chatter in blue or red force networks, changes in population sentiment, or curfew movement. CEDAR will also provide an integrated process to execute event queries that leverages our team's abilities in performing approximate pattern matching over multi-dimensional data. This capability enables us to mine sensor feeds at scale, such as detecting motion in video, non-verbal audio cues, such as gunfire, sentiment in text sources, and changes in human network activity. Finally, CEDAR will provide a suite of event projections to facilitate discriminating aggregate events that indicate complex activity. By combining event projections with semantic event scoring, we can assess if detected events are progressing on a "good" or "bad" vector and exploit this information to choose actions to modulate complex event behavior. Benefits: CEDAR's extensible framework for detecting and analyzing aggregated simple event indicators of complex event activities will improve the ability of analysts to understand activities with respect to insurgents, the local population, coalition forces, and the environment. By capturing analyst perceptions of perceived event intent, impact, and visibility, we can construct robust projections of event results to discriminate the trends of aggregate behavior in an area towards favorable or unfavorable outcomes. Such a system for detecting and analyzing complex event behavior is of immediate value to intelligence agencies seeking to suggest coalition actions based on multiple sensor inputs. In addition, the complex event analysis abilities of CEDAR will be of interest to government and commercial agencies seeking to combat fraud, understand how events affect logistics chains or other business processes, or to understand the influence of multiple events with respect to offensive and defensive actions in the cyber domain. Return