By Uffe Kock Wiil (auth.), Uffe Kock Wiil (eds.)
Since the Sept. 11 terrorist assaults within the usa, critical issues have been raised on family and overseas safety concerns. hence, there was substantial curiosity lately in technological recommendations and assets to counter acts of terrorism. during this context, this ebook offers a state of the art survey of the newest advances within the box of counterterrorism and open resource intelligence, demonstrating how a variety of latest in addition to novel instruments and methods might be utilized in scuffling with covert terrorist networks. a specific concentration is going to be on destiny demanding situations of open resource intelligence and views on tips to successfully function that allows you to hinder terrorist activities.
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Extra resources for Counterterrorism and Open Source Intelligence
Example text
P//. When is very large the path of least cost has a much higher probability than any of the alternatives, while close to 0 assigns all paths approximately the same probability. e. the sensitivity is low). A value of 0:1 means that if the terrorist group learns of a increase in path cost by 10 units, its probability of taking the path will decrease by a multiplicative factor of 2:72. The exact amount of change depends on the original path probability: it is not as great a decrease when the original probability is high.
Future work can develop network-theoretic methods to analyze how terrorist groups would bring those resources together while maintaining secrecy. It would also be possible to consider the risk of attacks by specific groups, including detailed model of their target preferences. g. human representatives such as diplomats or journalists and physical installations such embassies or business offices). Such foreign representatives give terrorist groups high-value targets without the risk of transnational attacks.
The area of a circle at coordinates (i; j ) is proportional to the number of plots from i to j . The bottom row indicates that the vast majority of plots target the US 4 Predictions One way of representing the solution of the model is through an attack risk matrix, the counterpart of the historical data matrix in Fig. 1. The model predicts (Fig. 3) that the United States would attract the bulk of transnational terrorism – all other countries are almost free of terrorism (small circles). The reason the United States is such a magnet is because of its vast geopolitical weight and relatively open borders.