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Information Systems Frontiers

Erschienen in:

01.03.2011

Computational approaches to suspicion in adversarial settings

verfasst von: David B. Skillicorn

Erschienen in: Information Systems Frontiers | Ausgabe 1/2011

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Abstract

Intelligence and law enforcement agencies collect large datasets, but have difficulty focusing analyst attention on the most significant records and structures within them. We address this problem using suspicion, which we interpret as relevant anomaly, as the measure associated with data records and individuals. For datasets collected about widespread activities in which the signs of adversarial activity are rare, we suggest ways to build predictive models of suspicion. For datasets collected as the result of lawful interception, we suggest a model of suspicion spreading using the social network implied by the intercepted data.

Vorheriger Artikel Tracking and disrupting dark networks: Challenges of data collection and analysis

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Titel: Computational approaches to suspicion in adversarial settings
verfasst von: David B. Skillicorn
Publikationsdatum: 01.03.2011
Verlag: Springer US
Erschienen in: Information Systems Frontiers / Ausgabe 1/2011
Print ISSN: 1387-3326
Elektronische ISSN: 1572-9419
DOI: https://doi.org/10.1007/s10796-010-9279-4

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