Identification of critical locations across multiple infrastructures for terrorist actions

This paper presents a possible approach to ranking geographic regions that can influence multiple infrastructures. Once ranked, decision makers can determine whether these regions are critical locations based on their susceptibility to terrorist acts. We identify these locations by calculating a value for a geographic region that represents the combined values to the decision makers of all the infrastructures crossing through that region. These values, as well as the size of the geographic region, are conditional on an assumed destructive threat of a given size. In our case study, the threat is assumed to be minor, e.g., a bomb that can affect objects within 7 m of it. This approach first requires an assessment of the users of the system. During this assessment, each user is assigned a performance index (PI) based on the disutility of the loss of each infrastructure's resource via multi-attribute utility theory (MAUT). A Monte Carlo network analysis is then performed to develop importance measures (IM) for the elements of each infrastructure for their ability to service each user. We combine the IMs with the user PIs to a value that we call valued worth (VW) for each infrastructure's elements independently. Then we use spatial analysis techniques within a geographic information system (GIS) to combine the VWs of each infrastructure's elements in a geographic area, conditional on the threat, into a total value we call geographic valued worth (GVW). The GVW is displayed graphically in the GIS system in a color scheme that shows the numerical ranking of these geographic areas. The map and rankings are then submitted to the decision makers to better allocate anti-terrorism resources. A case study of this methodology is performed on the Massachusetts Institute of Technology (MIT) campus. The results of the study show how the methodology can bring attention to areas that are important when several infrastructures are considered, but may be ignored when infrastructures are analyzed individually