Abstract
The spreading of dangerous malware in inter-dependent networks of electronics devices has raised deep concern, because from the ICT networks infections may propagate to other Critical Infrastructures producing the well-known domino effect. Researchers are attempting to develop a high level analysis of malware propagation, discarding software details, in order to generalize to the maximum extent the defensive strategies. It has been suggested that the maximum eigenvalue could act as a threshold for the malware’s spreading. In this paper we study the Italian Internet Autonomous System simulating the diffusion of a worm, verifying the theoretical threshold and showing how to choose in a sub-optimal way the set of most influential nodes to protect with respect to the spectral paradigm. Our algorithm is fast and outperforms measures as degree, closeness, betweenness, and dynamical importance.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Wang, Y., Chakrabarti, D., Wang, C., Faloutsos, C.: Epidemic Spreading in Real Networks. In: SRDS Conference (2003)
Chakrabarti, D., Wang, Y., Wang, C., Leskovec, J., Faloutsos, C.: Epidemic Thresholds in Real Networks. ACM Trans. Inform. Syst. Secur. 10 (2008)
Pastor-Satorras, R., Vespignani, A.: Epidemic Spreading in Scale-free Networks. Phy. Rev. Lett. 86(14), 3200–3203 (2001)
Buldyrev, S., Parshani, R., Paul, G., Stanley, G., Havlin, S.: Catastrophic Cascade of Failures in Interdependent Networks. Nature 464 (2010)
Rinaldi, J., et al.: Identifying Critical Infrastructure Interdependencies. IEEE Control System Magazine 21, 337–351 (2001)
Osorio, L.: Seismic Response of Critical Interdependent Networks. Earthquake Eng. Struct. Dyn. 36, 285–293 (2007)
Peng, C., Xiaogang, J., Meixia, S.: Epidemic Threshold and Immunization on Generalized Networks. Physica A 389, 549–560 (2010)
Fioriti, V., D’Agostino, G., Bologna, S.: On Modeling and Measuring Inter-dependencies among Critical Infrastructures. In: COMPENG 2010 IEEE Conference, Roma (2010)
Harris, C., Miles, J.: Stability of Linear Systems. Science and Engineering, vol. 153. Academic Press, London (1980)
Courtesy of E. Gregori and coworkers, CNR Pisa
Zesheng, C., Chuanyi, J.: Measuring Network Aware Worm Spreading Strategy. In: INFOCOM 26th IEEE International Conference on Computer Communications. IEEE (2007)
Fruchterman, T., Reingold, E.: Graph Drawing by Force-Directed Placement. Software Practice & Experience 21, 1129 (1999)
Chen, Z., Ji, C.: Measuring Network-Aware Worm Spreading Ability. In: IEEE INFOCOM Conference 2007 (2007)
Arulselvan, A., Commander, C.W., Elefteriadou, L., Pardalos, P.M.: Detecting Critical Nodes in Sparse Graphs. Comput. Oper. Res. 36(7), 2193–2200 (2009)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Arbore, A., Fioriti, V. (2013). Sub-optimal Topological Protection Strategy from Advanced Malware. In: Bologna, S., Hämmerli, B., Gritzalis, D., Wolthusen, S. (eds) Critical Information Infrastructure Security. CRITIS 2011. Lecture Notes in Computer Science, vol 6983. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41476-3_7
Download citation
DOI: https://doi.org/10.1007/978-3-642-41476-3_7
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-41475-6
Online ISBN: 978-3-642-41476-3
eBook Packages: Computer ScienceComputer Science (R0)