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Dynamics of Large-Scale Networks: Models, Empirical Analysis and Applications (An Adventure in Computer and Computational Epidemiology)
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| When |
May 26, 2009 from 12:00 PM to 02:00 PM |
| Where | Engr IV Room 57-124 |
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Joseph S. Kong
Advisor: Vwani P. Roychowdhury
Tuesday, May 26, 2009 at 12:00pm-2:00pm
Engr IV Room 57-124
Abstract:
Given a computer network, how does a trojan help the spread of other
malwares (malicious softwares)? On sexual contact networks, how do
sexually transmitted diseases (STDs) help the Human Immunodeficiency
Virus (HIV) spread? Moreover, reducing HIV incidences through STD
treatment is part of HIV prevention programs since the 1990's as
advocated by the World Health Organization (WHO). In fact,
understanding the synergistic spread of STD and HIV is explicitly listed
as an open problem in a Nature Reviews article recently. Faced with
such threats in computer security and public health, we are in need of
mathematical models to better understand these complex epidemic
dynamics. In this talk, I will show that these problems, which are from
seemingly completely different domains of computer security and public
health, can be modeled under a common framework as the spread of two
synergistic pathogens on a network. The synergy comes from the local
interaction, where if a node is infected with the trojan (or an STD),
the node becomes more susceptible to other malware (or HIV) by an
amplification factor. We develop an analytical methodology for modeling
the complex dual-pathogen epidemic spread on networks. Our analytical
results show how both the increased susceptibility engendered by
trojans, as well as, the heterogeneous structure of the underlying
network work together to significantly reduce the epidemic thresholds
for synergistic virus and ignite epidemics. In addition, we show that
employing the strategy to fight viral epidemics indirectly by combating
the trojan (or the STD) is likely to be ineffective, if only marginal
reduction in trojan (or STD) prevalence can be achieved. We demonstrate
the validity of our results on large-scale synthesized graphs and
real-world networks that include email, P2P, and online social networks,
where malwares are known to spread on a recurrent basis.
Biography:
Born in Guangzhou, China, Joseph S. Kong received the B.Sc. and M.Sc.
degree in electrical engineering from UCLA. His recent article on the
evolution of the World Wide Web has been featured on the cover of the
Proceedings of the National Academy of Sciences (PNAS).
