Back to Search Start Over

Layered defense: modeling terrorist transfer threat networks and optimizing network risk reduction.

Authors :
Taquechel, Eric
Source :
IEEE Network. 11/01/2010, Vol. 24 Issue 6, p30-35. 0p. 5 Diagrams.
Publication Year :
2010

Abstract

The security of the international maritime supply chain and United States ports is vital to the nation?s economy. Terrorists may exploit this supply chain to smuggle illicit people or material into the United States. This scenario, the terrorist transfer threat, has potentially catastrophic consequences. Lewis?s Model Based Risk Assessment software applies network theory to analyze terrorist threats against critical infrastructure systems. This article adapts MBRA to model the terrorist transfer threat?s propagation through the maritime supply chain. MBRA originally applied fault trees to model the inherited vulnerability of a network node based on the logic gate between it and lower layers of nodes (De Morgan?s Law). The author adapts MBRA to incorporate the organic vulnerability for each transfer threat network node in addition to the inherited vulnerability in order to model the decreased likelihood of the transfer threat propagating through the (supply chain) network. This adaptation produces recommendations for optimizing budget allocations across nodes to minimize overall network risk (measured in dollars). It can also show how subsequent manual budget reallocation can change network risk. The MBRA application uses emergent behavior to allocate money at random until equilibrium is reached and network risk is minimized. Return on investment for each network node is also calculated, representing how much network risk is reduced per dollar spent at that node. MBRA networks are indifferent as to whether intermediate or target nodes have maritime locations. Thus, the adapted approach has utility for both maritime and non-maritime homeland security authorities. [ABSTRACT FROM PUBLISHER]

Details

Language :
English
ISSN :
08908044
Volume :
24
Issue :
6
Database :
Academic Search Index
Journal :
IEEE Network
Publication Type :
Academic Journal
Accession number :
55209340
Full Text :
https://doi.org/10.1109/MNET.2010.5634440