TY - GEN
T1 - Smartphone viruses propagation on heterogeneous composite networks
AU - Wei, Xuetao
AU - Valler, Nicholas C.
AU - Faloutsos, Michalis
AU - Neamtiu, Iulian
AU - Prakash, B. Aditya
AU - Faloutsos, Christos
N1 - Copyright:
Copyright 2013 Elsevier B.V., All rights reserved.
PY - 2013
Y1 - 2013
N2 - Smartphones are now targets of malicious viruses. Furthermore, the increasing 'connectedness' of smartphones has resulted in new delivery vectors for malicious viruses, including proximity-, social- and other technology-based methods. In fact, Cabir and CommWarrior are two viruses-observed in the wild-that spread, at least in part, using proximity-based techniques (line-of-sight bluetooth radio). In this paper, we propose and evaluate SI 1I2S a competition model that describes the spread of two mutually exclusive viruses across heterogeneous composite networks, one static (social connections) and one dynamic (mobility pattern). To approximate dynamic network behavior, we use classic mobility models from ad hoc networking, e.g., Random Waypoint, Random Walk and Levy Flight. We analyze our model using techniques from dynamic systems and find that the first eigenvalue of the system matrices λs1, λs2 of the two networks (static and dynamic networks) appropriately captures the competitive interplay between two viruses and effectively predicts the competition's 'winner', which provides a feasible way to defend against smartphone viruses.
AB - Smartphones are now targets of malicious viruses. Furthermore, the increasing 'connectedness' of smartphones has resulted in new delivery vectors for malicious viruses, including proximity-, social- and other technology-based methods. In fact, Cabir and CommWarrior are two viruses-observed in the wild-that spread, at least in part, using proximity-based techniques (line-of-sight bluetooth radio). In this paper, we propose and evaluate SI 1I2S a competition model that describes the spread of two mutually exclusive viruses across heterogeneous composite networks, one static (social connections) and one dynamic (mobility pattern). To approximate dynamic network behavior, we use classic mobility models from ad hoc networking, e.g., Random Waypoint, Random Walk and Levy Flight. We analyze our model using techniques from dynamic systems and find that the first eigenvalue of the system matrices λs1, λs2 of the two networks (static and dynamic networks) appropriately captures the competitive interplay between two viruses and effectively predicts the competition's 'winner', which provides a feasible way to defend against smartphone viruses.
KW - Competition
KW - Epidemics
KW - Mobile Networks
KW - Social Networks
UR - http://www.scopus.com/inward/record.url?scp=84886018313&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84886018313&partnerID=8YFLogxK
U2 - 10.1109/NSW.2013.6609203
DO - 10.1109/NSW.2013.6609203
M3 - Conference contribution
AN - SCOPUS:84886018313
SN - 9781479904365
T3 - Proceedings of the 2013 IEEE 2nd International Network Science Workshop, NSW 2013
SP - 106
EP - 109
BT - Proceedings of the 2013 IEEE 2nd International Network Science Workshop, NSW 2013
T2 - 2013 IEEE 2nd International Network Science Workshop, NSW 2013
Y2 - 29 April 2013 through 1 May 2013
ER -