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We introduce a new Bayesian admixture model intended for exploratory analysis of communication networks—specifically, the discovery and visualization of topic-specific subnetworks in email data sets. Our model produces principled vi-sualizations of email networks, i.e., visualizations that have precise mathematical interpretations in terms of our model and(More)
Correlations between anomalous activity patterns can yield pertinent information about complex social processes: a significant deviation from normal behavior, exhibited simultaneously by multiple pairs of actors, provides evidence for some underlying relationship involving those pairs—i.e., a multilateral relation. We introduce a new nonparametric Bayesian(More)
We provide detailed measurement of the illegal trade in child exploitation material (CEM, also known as child pornography) from mid-2011 through 2014 on five popular peer-to-peer (P2P) file sharing networks. We characterize several observations: counts of peers trafficking in CEM; the proportion of arrested traffickers that were identified during the(More)
Anomaly detection systems are a promising tool to identify compromised user credentials and malicious insiders in enterprise networks. Most existing approaches for modelling user behaviour rely on either independent observations for each user or on pre-defined user peer groups. A method is proposed based on recommender system algorithms to learn overlapping(More)
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