Modeling and Restraining Mobile Virus Propagation

Viruses and malwares can spread from computer networks into mobile networks with the rapid growth of smart cellphone users. In a mobile network, viruses and malwares can cause privacy data leakage, extra charges, and remote listening. Furthermore, they can jam wireless servers by sending thousands of spam messages or track user positions through GPS. Because of the potential damages of mobile viruses, it is important for us to gain a deep understanding of the propagation mechanisms of mobile viruses. In this paper, we propose a two-layer network model for simulating virus propagation through both Bluetooth and SMS. Different from previous work, our work addresses the impacts of human behaviors, i.e., operational behavior and mobile behavior, on virus propagation. Our simulation results provide further insights into the determining factors of virus propagation in mobile networks. Moreover, we examine two strategies for restraining mobile virus propagation, i.e., preimmunization and adaptive dissemination strategies drawing on the methodology of autonomy-oriented computing (AOC). The experimental results show that our strategies can effectively protect large-scale and/or highly dynamic mobile networks.

[1]  Fan Zhang,et al.  Stealthy video capturer: a new video-based spyware in 3G smartphones , 2009, WiSec '09.

[2]  Sajal K. Das,et al.  This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. IEEE TRANSACTIONS ON MOBILE COMPUTING An Epidemic Theoretic Framework for Vulnerability Analysi , 2022 .

[3]  A. Gawande,et al.  The bell curve. , 2005, Minnesota medicine.

[4]  Julinda Stefa,et al.  SWIM: A Simple Model to Generate Small Mobile Worlds , 2008, IEEE INFOCOM 2009.

[5]  Alessandro Vespignani,et al.  Multiscale mobility networks and the spatial spreading of infectious diseases , 2009, Proceedings of the National Academy of Sciences.

[6]  Sencun Zhu,et al.  Designing System-Level Defenses against Cellphone Malware , 2009, 2009 28th IEEE International Symposium on Reliable Distributed Systems.

[7]  T. Geisel,et al.  Forecast and control of epidemics in a globalized world. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[8]  Sajal K. Das,et al.  Deployment-aware modeling of node compromise spread in wireless sensor networks using epidemic theory , 2009, TOSN.

[9]  Jiming Liu,et al.  Autonomy-Oriented Computing (AOC): The Nature and Implications of a Paradigm for Self-Organized Computing , 2008, 2008 Fourth International Conference on Natural Computation.

[10]  Albert-László Barabási,et al.  Understanding the Spreading Patterns of Mobile Phone Viruses , 2009, Science.

[11]  Kwang-Cheng Chen,et al.  On Modeling Malware Propagation in Generalized Social Networks , 2011, IEEE Communications Letters.

[12]  Alessandro Vespignani,et al.  Human Mobility Networks, Travel Restrictions, and the Global Spread of 2009 H1N1 Pandemic , 2011, PloS one.

[13]  Geoffrey M. Voelker,et al.  Defending Mobile Phones from Proximity Malware , 2009, IEEE INFOCOM 2009.

[14]  Sencun Zhu,et al.  A Social Network Based Patching Scheme for Worm Containment in Cellular Networks , 2009, IEEE INFOCOM 2009.

[15]  S. Chong,et al.  SLAW : A Mobility Model for Human Walks , 2009 .

[16]  Shweta Bansal,et al.  The dynamic nature of contact networks in infectious disease epidemiology , 2010, Journal of biological dynamics.

[17]  Beom Jun Kim,et al.  Attack vulnerability of complex networks. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.

[18]  Sencun Zhu,et al.  A systematic approach for cell-phone worm containment , 2008, WWW.

[19]  Geoffrey M. Voelker,et al.  Can you infect me now?: malware propagation in mobile phone networks , 2007, WORM '07.

[20]  Guanhua Yan,et al.  Modeling Propagation Dynamics of Bluetooth Worms (Extended Version) , 2009, IEEE Transactions on Mobile Computing.

[21]  Marta C. González,et al.  Understanding spatial connectivity of individuals with non-uniform population density , 2009, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[22]  Jiming Liu,et al.  Modeling and predicting the dynamics of mobile virus spread affected by human behavior , 2011, 2011 IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks.

[23]  Chaoming Song,et al.  Modelling the scaling properties of human mobility , 2010, 1010.0436.

[24]  Ning Zhong,et al.  Network immunization and virus propagation in email networks: experimental evaluation and analysis , 2010, Knowledge and Information Systems.

[25]  Kang G. Shin,et al.  Behavioral detection of malware on mobile handsets , 2008, MobiSys '08.

[26]  Donald F. Towsley,et al.  On distinguishing between Internet power law topology generators , 2002, Proceedings.Twenty-First Annual Joint Conference of the IEEE Computer and Communications Societies.

[27]  Ahmed Helmy,et al.  Modeling Time-Variant User Mobility in Wireless Mobile Networks , 2007, IEEE INFOCOM 2007 - 26th IEEE International Conference on Computer Communications.

[28]  Kang G. Shin,et al.  Detecting energy-greedy anomalies and mobile malware variants , 2008, MobiSys '08.

[29]  Alessandro Vespignani,et al.  Epidemic spreading in scale-free networks. , 2000, Physical review letters.

[30]  Hunter N. B. Moseley,et al.  Limits of Predictability in Human Mobility , 2010 .

[31]  Jie Wu,et al.  CPMC: An Efficient Proximity Malware Coping Scheme in Smartphone-based Mobile Networks , 2010, 2010 Proceedings IEEE INFOCOM.

[32]  Christos Faloutsos,et al.  Mobile call graphs: beyond power-law and lognormal distributions , 2008, KDD.

[33]  Injong Rhee,et al.  On the levy-walk nature of human mobility , 2011, TNET.

[34]  Shlomo Havlin,et al.  Finding a better immunization strategy. , 2008, Physical review letters.

[35]  Alessandro Vespignani,et al.  Phase transitions in contagion processes mediated by recurrent mobility patterns , 2011, Nature physics.

[36]  Donald F. Towsley,et al.  Modeling and Simulation Study of the Propagation and Defense of Internet E-mail Worms , 2007, IEEE Transactions on Dependable and Secure Computing.

[37]  Albert-László Barabási,et al.  Understanding individual human mobility patterns , 2008, Nature.

[38]  T. Geisel,et al.  The scaling laws of human travel , 2006, Nature.

[39]  Albert-László Barabási,et al.  Limits of Predictability in Human Mobility , 2010, Science.

[40]  Reuven Cohen,et al.  Efficient immunization strategies for computer networks and populations. , 2002, Physical review letters.

[41]  Ning Zhong,et al.  Network Immunization with Distributed Autonomy-Oriented Entities , 2011, IEEE Transactions on Parallel and Distributed Systems.

[42]  Binshan Lin,et al.  Security aspects of mobile phone virus: a critical survey , 2008, Ind. Manag. Data Syst..

[43]  Mark E. J. Newman,et al.  Technological Networks and the Spread of Computer Viruses , 2004, Science.

[44]  M. Newman Spread of epidemic disease on networks. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.

[45]  Pan Hui,et al.  Impact of Human Mobility on the Design of Opportunistic Forwarding Algorithms , 2006, Proceedings IEEE INFOCOM 2006. 25TH IEEE International Conference on Computer Communications.

[46]  Injong Rhee,et al.  SLAW: A New Mobility Model for Human Walks , 2009, IEEE INFOCOM 2009.

[47]  William H. Sanders,et al.  Quantifying the Effectiveness of Mobile Phone Virus Response Mechanisms , 2007, 37th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN'07).

[48]  Songwu Lu,et al.  Analysis of the Reliability of a Nationwide Short Message Service , 2007, IEEE INFOCOM 2007 - 26th IEEE International Conference on Computer Communications.

[49]  Songwu Lu,et al.  SmartSiren: virus detection and alert for smartphones , 2007, MobiSys '07.

[50]  A-L Barabási,et al.  Structure and tie strengths in mobile communication networks , 2006, Proceedings of the National Academy of Sciences.