What does the internet look like?
Which sub-graphs of such networks deviate from the "normal" (and are thus suspicious groups of people/nodes/routers)? How do we scale up all these algorithms, to handle graphs of millions and billions of nodes and edges?
These are the questions we address. Earlier work has shown that the topology of real networks presents some surprising patterns: the Internet topology obeys power-laws, and so does
the web topology. Both, along with social networks, they all exhibit "small world" phenomena. We present a list of such patterns that real graphs follow, as well as fast, scalable algorithms to efficiently process huge
datasets, in search of patterns and outliers.
BIOGRAPHICAL NOTE:
Christos Faloutsos is a Professor at Carnegie Mellon University. He has received the Presidential Young Investigator Award by
the National Science Foundation (1989),
five "best paper" awards, and several teaching awards. He is a member of the executive committee of SIGKDD; he has published over 120 refereed articles, one monograph, and holds five patents. His research interests include data mining
for streams and networks, fractals, indexing methods for spatial and multimedia bases, and data base performance.
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