Malware Avoidance Using Two Epidemic Layers
Keywords:
Malware, Malware Propagation, Two Layers, Power Law, Supervised ClassificationAbstract
Malware are malicious software programs deployed by cyber attackers to compromise computer. The solution to this problem is desperately desired by cyber defenders as the network security community does not yet have solid answers. The main scope of our project to investigate how malware propagate in networks from a global perspective. We propose a two layer malware propagation model to describe the development of a given malware at the Internet level. Compared with the existing single layer epidemic models, the proposed model represents malware propagation better in large-scale networks. We propose a two layer malware propagation model to describe the development of a given malware at the Internet level. Compared with the existing single layer epidemic models, the proposed model represents malware propagation better in large-scale networks
References
[1] B. Stone-Gross, M. Cova, L. Cavallaro, B.
Gilbert, M. Szydlowski, R. Kemmerer, C. Kruegel, and G. Vigna, “Your botnet is
my botnet: Analysis of a botnet takeover,†in CCS ’09: Proceedings of the 2009
ACM conference on computer communication security, 2009.
[2] D. Dagon, C. Zou, andW. Lee, “Modeling botnet
propagation using time zones,†in Proceedings of the 13 th Network and
Distributed System Security Symposium NDSS, 2006.
[3] M. A. Rajab, J. Zarfoss, F. Monrose, and A.
Terzis, “My botnet is bigger than yours (maybe, better than yours): why size
estimates remain challenging,†in Proceedings of the first conference on First
Workshop on Hot Topics in Understanding Botnets, 2007.
[4] D. Dagon, C. C. Zou, and W. Lee, “Modeling
botnet propagation using time zones,†in NDSS, 2006.
[5] A. M. Jeffrey, xiaohua Xia, and I. K. Craig,
“When to initiate hiv therapy: A control theoretic approach,†IEEE Transactions
on Biomedical Engineering, vol. 50, no. 11, pp. 1213–1220, 2003.
[6] R. Dantu, J.W. Cangussu, and S. Patwardhan,
“Fast worm containment using feedback control,†IEEE Transactions on Dependable
and Secure Computing, vol. 4, no. 2, pp. 119–136, 2007.
[7] S. H. Sellke, N. B. Shroff, and S. Bagchi,
“Modeling and automated containment of worms,†IEEE Trans. Dependable Sec.
Comput., vol. 5, no. 2, pp. 71–86, 2008.
[8] P. De, Y. Liu, and S. K. Das, “An epidemic
theoretic framework for vulnerability analysis of broadcast protocols in
wireless sensor networks,†IEEE Trans. Mob. Comput., vol. 8, no. 3, pp.
413–425, 2009.
[9] G. Yan and S. Eidenbenz, “Modeling propagation
dynamics of bluetooth worms (extended version),†IEEE Trans. Mob. Comput., vol.
8, no. 3, pp. 353–368, 2009.
[10] C. C. Zou, W. Gong, D. Towsley, and L. Gao,
“The monitoring and early detection of internet worms,†IEEE/ACM Trans. Netw.,
vol. 13, no. 5, pp. 961–974, 2005.Â
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