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Information technologies such as data mining and social network analysis have been widely used in law enforcement to solve crimes. Recent research indicates that geographic profiling also plays an important role in facilitating the investigation of crimes. However, lack of integration makes those systems less helpful in practice. In this paper, we propose an integrated system called PerpSearch that will take a given description of a crime, including its location, type, and the physical description of suspects (personal characteristics or vehicles) as input. To detect suspects, the system will process these inputs through four integrated components: geographic profiling, social network analysis, crime patterns, and physical matching. Essentially, geographic profiling determines "where" the suspects are, while other components determine "who" the suspects are. We then process the results using a score engine to give investigators a ranked list of individuals. To date, we have implemented a prototype of the system based on current Alabama law enforcement data.

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This paper describes an innovative Mobility Camouflaging Evaluation Tool (MCET) for mobile users traveling on a predefined geo-spatial graph. MCET is a customizable platform for evaluating the effectiveness of Mobility Camouflaging Algorithms (MCAs) and Adversary Observation Algorithms (AOAs). AOAs use observations of mobile user wireless transmissions to trace their movements. MCAs are designed to reduce the ability of AOAs to construct accurate traces. Specifically, MCAs camouflage the mobile user's movements by routing them "together" yet attempting to minimize the overhead of additional travel. The AOSs and MCAs that are developed by users and plugged into MCET produce tabular results for evaluation of mobile user movement logs that are also rendered in Google Earth.