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Abstract: We describe a guilt-by-association system that can be used to rank networked entities by their suspiciousness. We demonstrate the algorithm on a suite of data sets generated by a terrorist-world simulator developed to support a DoD program. Each data set consists of thousands of entities and some known links between them. The system ranks truly malicious entities highly, even if only relatively few are known to be malicious ex ante. When used as a tool for identifying promising data-gathering... (Update)
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BibTeX entry: (Update)
@misc{ and-suspicion,
author = "Collective Inference And",
title = "Suspicion scoring of networked entities based on guilt-by-association,",
url = "citeseer.ist.psu.edu/761706.html" }
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