Dynamic Topologies for Robust Scale-Free Networks
In recent years, the field of anonymity and traffic analysis have attracted much research interest. However, the analysis of subsequent dynamics of attack and defense, between an adversary using such topology information gleaned from traffic analysis to mount an attack, and defenders in a network, has recieved very little attention. Often an attacker tries to disconnect a network by destroying nodes or edges, while the defender counters using various resilience mechanisms. Examples include a music industry body attempting to close down a peer-to-peer file-sharing network; medics attempting to halt the spread of an infectious disease by selective vaccination; and a police agency trying to decapitate a terrorist organisation. Albert, Jeong and Barabási famously analysed the static case, and showed that vertex-order attacks are effective against scale-free networks. We extend this work to the dynamic case by developing a framework to explore the interaction of attack and defence strategies. We show, first, that naive defences don’t work against vertex-order attack; second, that defences based on simple redundancy don’t work much better, but that defences based on cliques work well; third, that attacks based on centrality work better against clique defences than vertex-order attacks do; and fourth, that defences based on complex strategies such as delegation plus clique resist centrality attacks better than simple clique defences. Our models thus build a bridge between network analysis and traffic analysis, and provide a framework for analysing defence and attack in networks where topology matters. They suggest definitions of efficiency of attack and defence, and may even explain the evolution of insurgent organisations from networks of cells to a more virtual leadership that facilitates operations rather than directing them. Finally, we draw some conclusions and present possible directions for future research.
KeywordsScale-free networks robustness covert groups topology security
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- 5.Ballester, C., Calvó-Armengol, A., Zenou, Y.: Who’s Who in Crime Networks – Wanted the Key Player, IUI Working Paper Series 617, The Research Institute of Industrial Economics (2004)Google Scholar
- 13.Jackson, M.O.: A Survey of Models of Network Formation: Stability and Efficiency A. In: Demange, G., Wooders, M. (eds.) Group Formation in Economics: Networks, Clubs, and Coalitions, Cambridge University Press, CambridgeGoogle Scholar
- 14.Krebs, V.E.: Mapping Networks of Terrorist Cells. Connections 12(3), http://www.locative.net/tcmreader/index.php?mapping;krebs
- 15.Holme, P., Kim, B.J., Yoon, C.N., Han, S.K.: Attack Vulnerability of Complex Networks. Phys. Rev. E 65, art. no. 018101 (2002)Google Scholar
- 16.Milgram, S.: The Small World Problem. Psychology Today 2, 60–87 (1967)Google Scholar
- 18.Sparrow, M.K.: The Application of Network Analysis to Criminal Intelligence: An assessment of the prospects. Social Networks 13, 253–274 (1990)Google Scholar
- 19.Thompson, N.: The Network Effect – Why Senegal’s bold anti-AIDS program is working. The Boston Globe (January 5, 2003), http://www.newamerica.net/index.cfm?pg=article&DocID=1092
- 21.Watts, D.J.: Six Degrees: The Science of a Connected Age. Norton, New York (2003)Google Scholar
- 23.Zhao, L.A., Park, K.H., Lai, Y.C.: Attack vulnerability of scale-free networks due to cascading breakdown. Physical review E 70, 035101 (R) (2004)Google Scholar