Identification of critical locations across multiple infrastructures for terrorist actions
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Nuclear Engineering, 2005. === Includes bibliographical references (leaves 59-60). === This paper discusses a possible approach to ranking geographic regions that can influence multiple infrastructures. Once ranked, decision makers can d...
Main Author: | |
---|---|
Other Authors: | |
Format: | Others |
Language: | English |
Published: |
Massachusetts Institute of Technology
2006
|
Subjects: | |
Online Access: | http://hdl.handle.net/1721.1/34445 |
id |
ndltd-MIT-oai-dspace.mit.edu-1721.1-34445 |
---|---|
record_format |
oai_dc |
spelling |
ndltd-MIT-oai-dspace.mit.edu-1721.1-344452019-05-02T15:51:17Z Identification of critical locations across multiple infrastructures for terrorist actions Patterson, Sean A. (Sean Albert), 1981- George E. Apostolakis. Massachusetts Institute of Technology. Dept. of Nuclear Engineering. Massachusetts Institute of Technology. Dept. of Nuclear Engineering. Nuclear Engineering. Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Nuclear Engineering, 2005. Includes bibliographical references (leaves 59-60). This paper discusses 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 which 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 regions, are conditional on a minor destructive threat of a given size, e.g,. a bomb that can affect objects within 15 feet 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. (cont.) 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 graphically displayed 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 preformed on the Massachusetts Institute of Technology's (MIT) campus. The results of the study show how the methodology can bring attention to areas that may be ignored through individual infrastructure analysis. The intersections of major infrastructures on the campus prove to be of the most importance to the stakeholders of the campus. by Sean Albert Patterson. S.M. 2006-11-07T12:11:27Z 2006-11-07T12:11:27Z 2005 2005 Thesis http://hdl.handle.net/1721.1/34445 70691166 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 68 leaves 4109502 bytes 4112273 bytes application/pdf application/pdf application/pdf Massachusetts Institute of Technology |
collection |
NDLTD |
language |
English |
format |
Others
|
sources |
NDLTD |
topic |
Nuclear Engineering. |
spellingShingle |
Nuclear Engineering. Patterson, Sean A. (Sean Albert), 1981- Identification of critical locations across multiple infrastructures for terrorist actions |
description |
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Nuclear Engineering, 2005. === Includes bibliographical references (leaves 59-60). === This paper discusses 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 which 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 regions, are conditional on a minor destructive threat of a given size, e.g,. a bomb that can affect objects within 15 feet 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. === (cont.) 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 graphically displayed 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 preformed on the Massachusetts Institute of Technology's (MIT) campus. The results of the study show how the methodology can bring attention to areas that may be ignored through individual infrastructure analysis. The intersections of major infrastructures on the campus prove to be of the most importance to the stakeholders of the campus. === by Sean Albert Patterson. === S.M. |
author2 |
George E. Apostolakis. |
author_facet |
George E. Apostolakis. Patterson, Sean A. (Sean Albert), 1981- |
author |
Patterson, Sean A. (Sean Albert), 1981- |
author_sort |
Patterson, Sean A. (Sean Albert), 1981- |
title |
Identification of critical locations across multiple infrastructures for terrorist actions |
title_short |
Identification of critical locations across multiple infrastructures for terrorist actions |
title_full |
Identification of critical locations across multiple infrastructures for terrorist actions |
title_fullStr |
Identification of critical locations across multiple infrastructures for terrorist actions |
title_full_unstemmed |
Identification of critical locations across multiple infrastructures for terrorist actions |
title_sort |
identification of critical locations across multiple infrastructures for terrorist actions |
publisher |
Massachusetts Institute of Technology |
publishDate |
2006 |
url |
http://hdl.handle.net/1721.1/34445 |
work_keys_str_mv |
AT pattersonseanaseanalbert1981 identificationofcriticallocationsacrossmultipleinfrastructuresforterroristactions |
_version_ |
1719029405460725760 |