We apply adjacency matrix clustering to network attack graphs for attack correlation, prediction, and hypothesizing. We self-multiply the clustered adjacency matrices to show atta...
How much can we infer about the pronunciation of a language – past or present – by observing which words its speakers rhyme? This paper explores the connection between pronunc...
We consider the problem of releasing a limited public view of a sensitive graph which reveals at least k edges per node. We are motivated by Facebook’s public search listings, w...
Most of the existing literature on empirical studies of Online Social Networks (OSNs) have focused on characterizing and modeling the structure of their inferred friendship graphs...
Based on a recent development in the area of error control coding, we introduce the notion of convolutional factor graphs (CFGs) as a new class of probabilistic graphical models. ...