161 research outputs found
Ranking Spaces for Predicting Human Movement in an Urban Environment
A city can be topologically represented as a connectivity graph, consisting
of nodes representing individual spaces and links if the corresponding spaces
are intersected. It turns out in the space syntax literature that some defined
topological metrics can capture human movement rates in individual spaces. In
other words, the topological metrics are significantly correlated to human
movement rates, and individual spaces can be ranked by the metrics for
predicting human movement. However, this correlation has never been well
justified. In this paper, we study the same issue by applying the weighted
PageRank algorithm to the connectivity graph or space-space topology for
ranking the individual spaces, and find surprisingly that (1) the PageRank
scores are better correlated to human movement rates than the space syntax
metrics, and (2) the underlying space-space topology demonstrates small world
and scale free properties. The findings provide a novel justification as to why
space syntax, or topological analysis in general, can be used to predict human
movement. We further conjecture that this kind of analysis is no more than
predicting a drunkard's walking on a small world and scale free network.
Keywords: Space syntax, topological analysis of networks, small world, scale
free, human movement, and PageRankComment: 11 pages, 5 figures, and 2 tables, English corrections from version 1
to version 2, major changes in the section of introduction from version 2 to
Quasi-stationary distributions as centrality measures of reducible graphs
Random walk can be used as a centrality measure of a directed graph. However,
if the graph is reducible the random walk will be absorbed in some subset of
nodes and will never visit the rest of the graph. In Google PageRank the
problem was solved by introduction of uniform random jumps with some
probability. Up to the present, there is no clear criterion for the choice this
parameter. We propose to use parameter-free centrality measure which is based
on the notion of quasi-stationary distribution. Specifically we suggest four
quasi-stationary based centrality measures, analyze them and conclude that they
produce approximately the same ranking. The new centrality measures can be
applied in spam detection to detect ``link farms'' and in image search to find
photo albums
Weighted citation: An indicator of an article's prestige
We propose using the technique of weighted citation to measure an article's
prestige. The technique allocates a different weight to each reference by
taking into account the impact of citing journals and citation time intervals.
Weighted citation captures prestige, whereas citation counts capture
popularity. We compare the value variances for popularity and prestige for
articles published in the Journal of the American Society for Information
Science and Technology from 1998 to 2007, and find that the majority have
comparable status.Comment: 17 pages, 6 figure
Graph-theoretic characterization of cyber-threat infrastructures
In this paper, we investigate cyber-threats and the underlying infrastructures. More precisely, we detect and analyze cyber-threat infrastructures for the purpose of unveiling key players (owners, domains, IPs, organizations, malware families, etc.) and the relationships between these players. To this end, we propose metrics to measure the badness of different infrastructure elements using graph theoretic concepts such as centrality concepts and Google PageRank. In addition, we quantify the sharing of infrastructure elements among different malware samples and families to unveil potential groups that are behind specific attacks. Moreover, we study the evolution of cyber-threat infrastructures over time to infer patterns of cyber-criminal activities. The proposed study provides the capability to derive insights and intelligence about cyber-threat infrastructures. Using one year dataset, we generate notable results regarding emerging threats and campaigns, important players behind threats, linkages between cyber-threat infrastructure elements, patterns of cyber-crimes, etc
- …