10.1073/pnas.0811973106 In densely populated urban areas WiFi routers form a tightly interconnected proximity network that can be exploited as a substrate for the spreading of malware able to launch massive fraudulent attacks. In this article, we consider several scenarios for the deployment of malware that spreads over the wireless channel of major urban areas in the US. We develop an epidemiological model that takes into consideration prevalent security flaws on these routers. The spread of such a contagion is simulated on real-world data for georeferenced wireless routers. We uncover a major weakness of WiFi networks in that most of the simulated scenarios show tens of thousands of routers infected in as little as 2 weeks, with the majority of the infections occurring in the first 24–48 h. We indicate possible containment and prevention measures and provide computational estimates for the rate of encrypted routers that would stop the spreading of the epidemics by placing the system below the percolation threshold.
%0 Journal Article
%1 citeulike:3973589
%A Hu, Hao
%A Myers, Steven
%A Colizza, Vittoria
%A Vespignani, Alessandro
%D 2009
%J Proceedings of the National Academy of Sciences
%K citeulike epidemis, malware, propagacin, seguridad, virus, wifi
%N 5
%P 1318--1323
%R 10.1073/pnas.0811973106
%T WiFi networks and malware epidemiology
%U http://dx.doi.org/10.1073/pnas.0811973106
%V 106
%X 10.1073/pnas.0811973106 In densely populated urban areas WiFi routers form a tightly interconnected proximity network that can be exploited as a substrate for the spreading of malware able to launch massive fraudulent attacks. In this article, we consider several scenarios for the deployment of malware that spreads over the wireless channel of major urban areas in the US. We develop an epidemiological model that takes into consideration prevalent security flaws on these routers. The spread of such a contagion is simulated on real-world data for georeferenced wireless routers. We uncover a major weakness of WiFi networks in that most of the simulated scenarios show tens of thousands of routers infected in as little as 2 weeks, with the majority of the infections occurring in the first 24–48 h. We indicate possible containment and prevention measures and provide computational estimates for the rate of encrypted routers that would stop the spreading of the epidemics by placing the system below the percolation threshold.
@article{citeulike:3973589,
abstract = {{10.1073/pnas.0811973106 In densely populated urban areas WiFi routers form a tightly interconnected proximity network that can be exploited as a substrate for the spreading of malware able to launch massive fraudulent attacks. In this article, we consider several scenarios for the deployment of malware that spreads over the wireless channel of major urban areas in the US. We develop an epidemiological model that takes into consideration prevalent security flaws on these routers. The spread of such a contagion is simulated on real-world data for georeferenced wireless routers. We uncover a major weakness of WiFi networks in that most of the simulated scenarios show tens of thousands of routers infected in as little as 2 weeks, with the majority of the infections occurring in the first 24–48 h. We indicate possible containment and prevention measures and provide computational estimates for the rate of encrypted routers that would stop the spreading of the epidemics by placing the system below the percolation threshold.}},
added-at = {2017-09-08T10:52:59.000+0200},
author = {Hu, Hao and Myers, Steven and Colizza, Vittoria and Vespignani, Alessandro},
biburl = {https://www.bibsonomy.org/bibtex/263dafdab83510057c98ee243d437055c/fernand0},
citeulike-article-id = {3973589},
citeulike-linkout-0 = {http://dx.doi.org/10.1073/pnas.0811973106},
citeulike-linkout-1 = {http://www.pnas.org/content/0811973106v1//.abstract},
citeulike-linkout-2 = {http://www.pnas.org/content/0811973106v1//.full.pdf},
citeulike-linkout-3 = {http://view.ncbi.nlm.nih.gov/pubmed/19171909},
citeulike-linkout-4 = {http://www.hubmed.org/display.cgi?uids=19171909},
day = 3,
doi = {10.1073/pnas.0811973106},
interhash = {246ea2e2016df4bba9383b1cedf3df70},
intrahash = {63dafdab83510057c98ee243d437055c},
journal = {Proceedings of the National Academy of Sciences},
keywords = {citeulike epidemis, malware, propagacin, seguridad, virus, wifi},
month = feb,
number = 5,
pages = {1318--1323},
pmid = {19171909},
posted-at = {2009-01-28 17:04:02},
priority = {2},
timestamp = {2017-09-08T10:53:23.000+0200},
title = {{WiFi networks and malware epidemiology}},
url = {http://dx.doi.org/10.1073/pnas.0811973106},
volume = 106,
year = 2009
}