ISBN: 9781249594796 - characterizing and detecting unrevealed elements of network systems (14 risultati)

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Taschenbuch. Condizione: Neu. Neuware - This dissertation addresses the problem of discovering and characterizing unknown elements in network systems. It is not uncommon to have incomplete knowledge of network systems due to either passive circumstances, e.g. limited resources to observe a network, or active circumstances, e.g. intentional acts of concealment, or some combination of active and passive influences. This research suggests statistical and graph theoretic approaches for such situations, including those in which nodes are causally related. A related aspect of this research is accuracy assessment. It is possible an analyst could fail to detect a network element, or be aware of network elements, but incorrectly conclude the associated network system structure. Consequently, this dissertation provides a framework to evaluate accuracy.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant. …

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