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Issue No.08 - Aug. (2013 vol.24)
pp: 1633-1643
Sheng Wen , Central South University, Changsha and Deakin University, Melbourne
Wei Zhou , Central South University, Changsha and Deakin University, Melbourne
Jun Zhang , Deakin University, Melbourne
Yang Xiang , Deakin University, Melbourne
Wanlei Zhou , Deakin University, Melbourne
Weijia Jia , City University of Hong Kong, Hong Kong
Social network worms, such as email worms and facebook worms, pose a critical security threat to the Internet. Modeling their propagation dynamics is essential to predict their potential damages and develop countermeasures. Although several analytical models have been proposed for modeling propagation dynamics of social network worms, there are two critical problems unsolved: temporal dynamics and spatial dependence. First, previous models have not taken into account the different time periods of Internet users checking emails or social messages, namely, temporal dynamics. Second, the problem of spatial dependence results from the improper assumption that the states of neighboring nodes are independent. These two problems seriously affect the accuracy of the previous analytical models. To address these two problems, we propose a novel analytical model. This model implements a spatial-temporal synchronization process, which is able to capture the temporal dynamics. Additionally, we find the essence of spatial dependence is the spreading cycles. By eliminating the effect of these cycles, our model overcomes the computational challenge of spatial dependence and provides a stronger approximation to the propagation dynamics. To evaluate our susceptible-infectious-immunized (SII) model, we conduct both theoretical analysis and extensive simulations. Compared with previous epidemic models and the spatial-temporal model, the experimental results show our SII model achieves a greater accuracy. We also compare our model with the susceptible-infectious-susceptible and susceptible-infectious-recovered models. The results show that our model is more suitable for modeling the propagation of social network worms.
Social network services, Grippers, Computational modeling, Topology, Analytical models, Network topology, Electronic mail, propagation dynamics, Social network services, Grippers, Computational modeling, Topology, Analytical models, Network topology, Electronic mail, modeling, Security, social network worms
Sheng Wen, Wei Zhou, Jun Zhang, Yang Xiang, Wanlei Zhou, Weijia Jia, "Modeling Propagation Dynamics of Social Network Worms", IEEE Transactions on Parallel & Distributed Systems, vol.24, no. 8, pp. 1633-1643, Aug. 2013, doi:10.1109/TPDS.2012.250
[1] M.E.J. Newman, Networks: An Introduction, pp. 36-39, Oxford, 2010.
[2] N. Weaver, V. Paxson, S. Staniford, and R. Cunningham, "A Taxonomy of Computer Worms," Proc. First ACM Workshop Rapid Malcode (WORM '03), Oct. 2003.
[3] H. Ebel, L. Mielsch, and S. Bornholdt, "Scale-Free Topology of E-Mail Networks," Physical Rev. E, vol. 66, 2002.
[4] A. Mislove, M. Marcon, K.P. Gummadi, P. Druschel, and B. Bhattacharjee, "Measurement and Analysis of Online Social Networks," Proc. ACM SIGCOMM, 2007.
[5] R. Pastor-Satorras and A. Vespignani, "Epidemic Spreading in Scale-Free Networks," Physical Rev. Letters, vol. 86, pp. 3200-3203, 2001.
[6] Y. Moreno, J.B. Gomez, and A.F. Pacheco, "Epidemic Incidence in Correlated Complex Networks," Physical Rev. E, vol. 68, 2003.
[7] Y. Moreno, R. Pastor-Satorras, and A. Vespignani, "Epidemic Outbreaks in Complex Heterogeneous Networks," European Physical J. B, vol. 26, pp. 521-529, 2002.
[8] M. Boguna, R. Pastor-Satorras, and A. Vespignani, "Epidemic Spreading in Complex Networks with Degree Correlations," Statistical Mechanics of Complex Networks, vol. 625, pp. 127-147, 2003.
[9] R. Thommes and M. Coates, "Epidemiological Modeling of Peer-to-Peer Viruses and Pollution," Proc. IEEE INFOCOM, pp. 1-12, 2006.
[10] D. Chakrabarti, J. Leskovec, C. Faloutsos, S. Madden, C. Guestrin, and M. Faloutsos, "Information Survival Threshold in Sensor and p2p Networks," Proc. IEEE INFOCOM, pp. 1316-1324, 2007.
[11] A. Ganesh, L. Massoulie, and D. Towsley, "The Effect of Network Topology on the Spread of Epidemics," Proc. IEEE INFOCOM, pp. 1455-1466, 2005.
[12] Y. Wang, D. Chakrabarti, C. Wang, and C. Faloutsos, "Epidemic Spreading in Real Networks: An Eigenvalue Viewpoint," Proc. IEEE Symp. Reliable Distributed Systems, pp. 25-34, 2003.
[13] Z. Chen and C. Ji, "Spatial-Temporal Modeling of Malware Propagation in Networks," IEEE Trans. Neural Networks, vol. 16, no. 5, pp. 1291-1303, Sept. 2005.
[14] C.C. Zou, D. Towsley, and W. Gong, "Modeling and Simulation Study of the Propagation and Defense of Internet E-mail Worms," IEEE Trans. Dependable and Secure Computing, vol. 4, no. 2, pp. 105-118, Apr.-June 2007.
[15] G. Yan, G. Chen, S. Eidenbenz, and N. Li, "Malware Propagation in Online Social Networks: Nature, Dynamics, and Defense Implications," Proc. Sixth ACM Symp. Information Computer Comm. and Security (ASIACCS '11), 2011.
[16] W. Fan and K. Yeung, "Online Social Networks Paradise of Computer Viruses," Physics A: Statistical Mechanics and its Applications, vol. 390, pp. 189-197, 2011.
[17] X. Fan and Y. Xiang, "Modeling the Propagation of Peer-to-Peer Worms," Future Generation Computer Systems, vol. 26, pp. 1433-1443, 2010.
[18] S.M. Cheng, W. Ao, P.Y. Chen, and K.C. Chen, "On Modeling Malware Propagation in Generalized Social Networks," IEEE Comm. Letters, vol. 15, no. 1, pp. 25-27, Jan. 2011.
[19] Y.Y. Ahn, S. Han, H. Kwak, S. Moon, and H. Jeong, "Analysis of Topological Characteristics of Huge Online Social Networking Services," Proc. ACM Int'l Conf. World Wide Web (WWW '07), 2007.
[20] Y. Wang, S. Wen, S. Cesare, W. Zhou, and Y. Xiang, "Eliminating Errors in Worm Propagation Models," IEEE Comm. Letters, vol. 15, no. 9, pp. 1022-1024, Sept. 2011.
[21] M. Fossi and J. Blackbird, "Symantec Internet Security Threat Report 2010," technical report, Symantec Corp., Mar. 2011.
[22] M.E.J Newman, S. Forrest, and J. Balthrop, "Email Networks and the Spread of Computer Viruses," Physical Rev. E, vol. 66, 2002.
[23] S. Wen, W. Zhou, Y. Wang, W.L. Zhou, and Y. Xiang, "Locating Defense Positions for Thwarting the Propagation of Topological Worms," IEEE Comm. Letters, vol. 16, no. 4, pp. 560-563, Apr. 2012.
[24] M. Newman, "A Measure of Betweenness Centrality Based on Random Walks," Social Networks, vol. 27, pp. 39-54, 2005.
[25] Z. Chen, L. Gao, and K. Kwiat, "Modelling the Spread of Active Worms," Proc. IEEE INFOCOM, pp. 1890-1900, 2003.
[26] C.C. Zou, W. Gong, and D. Towsley, "Code Red Worm Propagation Modelling and Analysis," Proc. Ninth ACM Computer and Comm. Security Conf. (CCS '02), pp. 138-147, 2002.
[27] Y. Xiang, X. Fan, and W. Zhu, "Propagation of Active Worms: A Survey," Int'l J. Computer Systems Science and Eng., vol. 24, pp. 157-172, 2009.
[28] C.C. Zou, D. Towsley, and W. Gong, "On the Performance of Internet Worm Scanning Strategies," Performance Evaluation, vol. 63, pp. 700-723, 2006.
[29] P. Mahadevan, D. Krioukov, K. Fall, and A. Vahdat, "Systematic Topology Analysis and Generation Using Degree Correlations," Proc. ACM SIGCOMM, 2006.
[30] G. Yan, H.D. Flores, L. Cuellar, N. Hengartner, S. Eidenbenz, and V. Vu, "Bluetooth Worm Propagation: Mobility Pattern Matters," Proc. Second ACM Symp. Information Computer and Comm. Security (ASIACCS '07), 2007.
[31] G. Yan and S. Eidenbenz, "Modeling Propagation Dynamics of Bluetooth Worms (Extended Version)," IEEE Trans. Mobile Computing, vol. 8, no. 3, pp. 353-367, Mar. 2009.
[32] C. Gao, J. Liu, and N. Zhong, "Network Immunization and Virus Propagation in Email Networks: Experimental Evaluation and Analysis," Knowledge and Information Syst., vol. 27, pp. 253-279, 2011.
[33] M.C. Calzarossa and E. Gelenbe, Performance Tools and Applications to Networked Systems: Revised Tutorial Lectures. Springer-Verlag, 2004.
[34] Moore and C. Shannon, "The Nyxem Email Virus: Analysis and Inferences," technical report, CAIDA, Feb. 2006.
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