Literature DB >> 19342553

Understanding the spreading patterns of mobile phone viruses.

Pu Wang1, Marta C González, César A Hidalgo, Albert-László Barabási.   

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.

Entities:  

Mesh:

Year:  2009        PMID: 19342553     DOI: 10.1126/science.1167053

Source DB:  PubMed          Journal:  Science        ISSN: 0036-8075            Impact factor:   47.728


  58 in total

1.  Heterogeneous node responses to multi-type epidemics on networks.

Authors:  S Moore; T Rogers
Journal:  Proc Math Phys Eng Sci       Date:  2020-11-04       Impact factor: 2.704

2.  Understanding metropolitan patterns of daily encounters.

Authors:  Lijun Sun; Kay W Axhausen; Der-Horng Lee; Xianfeng Huang
Journal:  Proc Natl Acad Sci U S A       Date:  2013-08-05       Impact factor: 11.205

3.  Maximizing multiple influences and fair seed allocation on multilayer social networks.

Authors:  Yu Chen; Wei Wang; Jinping Feng; Ying Lu; Xinqi Gong
Journal:  PLoS One       Date:  2020-03-12       Impact factor: 3.240

4.  Predicting traffic volumes and estimating the effects of shocks in massive transportation systems.

Authors:  Ricardo Silva; Soong Moon Kang; Edoardo M Airoldi
Journal:  Proc Natl Acad Sci U S A       Date:  2015-04-20       Impact factor: 11.205

5.  Detecting and modelling real percolation and phase transitions of information on social media.

Authors:  Jiarong Xie; Fanhui Meng; Jiachen Sun; Xiao Ma; Gang Yan; Yanqing Hu
Journal:  Nat Hum Behav       Date:  2021-04-01

6.  Local structure can identify and quantify influential global spreaders in large scale social networks.

Authors:  Yanqing Hu; Shenggong Ji; Yuliang Jin; Ling Feng; H Eugene Stanley; Shlomo Havlin
Journal:  Proc Natl Acad Sci U S A       Date:  2018-07-03       Impact factor: 11.205

7.  Limits of social mobilization.

Authors:  Alex Rutherford; Manuel Cebrian; Sohan Dsouza; Esteban Moro; Alex Pentland; Iyad Rahwan
Journal:  Proc Natl Acad Sci U S A       Date:  2013-04-01       Impact factor: 11.205

8.  Evaluating the privacy properties of telephone metadata.

Authors:  Jonathan Mayer; Patrick Mutchler; John C Mitchell
Journal:  Proc Natl Acad Sci U S A       Date:  2016-05-17       Impact factor: 11.205

9.  Scaling identity connects human mobility and social interactions.

Authors:  Pierre Deville; Chaoming Song; Nathan Eagle; Vincent D Blondel; Albert-László Barabási; Dashun Wang
Journal:  Proc Natl Acad Sci U S A       Date:  2016-06-06       Impact factor: 11.205

10.  Dynamic social community detection and its applications.

Authors:  Nam P Nguyen; Thang N Dinh; Yilin Shen; My T Thai
Journal:  PLoS One       Date:  2014-04-10       Impact factor: 3.240

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.