%0 Journal Article %1 Wang2009Understanding %A Wang, Pu %A González, Marta C. %A Hidalgo, Cesar A. %A Barabási, Albert-Laszlo %D 2009 %I American Association for the Advancement of Science %J Science %K temporal\_networks, networks social-networks epidemics mobile-phones weighted-networks %N 5930 %P 1071--1076 %R 10.1126/science.1167053 %T Understanding the Spreading Patterns of Mobile Phone Viruses %U http://dx.doi.org/10.1126/science.1167053 %V 324 %X We modeled the mobility of mobile phone users in order to study the fundamental spreading patterns that characterize a mobile virus outbreak. We find that although Bluetooth viruses can reach all susceptible handsets with time, they spread slowly because of human mobility, offering ample opportunities to deploy antiviral software. In contrast, viruses using multimedia messaging services could infect all users in hours, but currently a phase transition on the underlying call graph limits them to only a small fraction of the susceptible users. These results explain the lack of a major mobile virus breakout so far and predict that once a mobile operating system's market share reaches the phase transition point, viruses will pose a serious threat to mobile communications.

@article{Wang2009Understanding, abstract = {{We modeled the mobility of mobile phone users in order to study the fundamental spreading patterns that characterize a mobile virus outbreak. We find that although Bluetooth viruses can reach all susceptible handsets with time, they spread slowly because of human mobility, offering ample opportunities to deploy antiviral software. In contrast, viruses using multimedia messaging services could infect all users in hours, but currently a phase transition on the underlying call graph limits them to only a small fraction of the susceptible users. These results explain the lack of a major mobile virus breakout so far and predict that once a mobile operating system's market share reaches the phase transition point, viruses will pose a serious threat to mobile communications.}}, added-at = {2019-06-10T14:53:09.000+0200}, author = {Wang, Pu and Gonz\'{a}lez, Marta C. and Hidalgo, Cesar A. and Barab\'{a}si, Albert-Laszlo}, biburl = {https://www.bibsonomy.org/bibtex/2042342f1cd7bd4e2834e49bf8edfebe2/nonancourt}, citeulike-article-id = {4269767}, citeulike-linkout-0 = {http://dx.doi.org/10.1126/science.1167053}, citeulike-linkout-1 = {http://www.sciencemag.org/content/324/5930/1071.abstract}, citeulike-linkout-2 = {http://www.sciencemag.org/content/324/5930/1071.full.pdf}, citeulike-linkout-3 = {http://www.sciencemag.org/cgi/content/abstract/1167053//}, citeulike-linkout-4 = {http://view.ncbi.nlm.nih.gov/pubmed/19342553}, citeulike-linkout-5 = {http://www.hubmed.org/display.cgi?uids=19342553}, day = 22, doi = {10.1126/science.1167053}, interhash = {314822057273399c0420e18e1bde5527}, intrahash = {042342f1cd7bd4e2834e49bf8edfebe2}, issn = {1095-9203}, journal = {Science}, keywords = {temporal\_networks, networks social-networks epidemics mobile-phones weighted-networks}, month = may, number = 5930, pages = {1071--1076}, pmid = {19342553}, posted-at = {2009-05-25 10:16:22}, priority = {2}, publisher = {American Association for the Advancement of Science}, timestamp = {2019-08-20T16:57:00.000+0200}, title = {{Understanding the Spreading Patterns of Mobile Phone Viruses}}, url = {http://dx.doi.org/10.1126/science.1167053}, volume = 324, year = 2009 }