A novel framework for mobile attack strategy modelling and vulnerability analysis in wireless ad hoc networks

International Journal of Security and Networks

Volumn 1, Issue 3-4, 2006, Pages 255-265

  Karyotis, Vasileios ^a   Papavassiliou, Symeon ^a   Grammatikou, Mary ^a   Maglaris, Vasilis ^a  

^a NATIONAL TECHNICAL UNIVERSITY OF ATHENS NTUA   (Greece)

Author keywords

attack modelling and propagation; security; vulnerability analysis; wireless ad hoc networks

Indexed keywords

EID: 44649095872     PISSN: 17478405     EISSN: 17478413     Source Type: Journal    
DOI: 10.1504/ijsn.2006.011785     Document Type: Article

References (21)

1. Chen, Z., Gao, L. and Kwiat, K. (2003) ‘Modeling the spread of active worms’, Proceedings of the 22nd IEEE Conference on Computer Communications (INFOCOM), Miami, FL, April, Vol. III, pp.1890–1900.
2. F-secure website (2004) Available at: http://www.f-secure.com/v-descs/cabir.shtml.
3. Ganesh, A., Massoulie, L. and Towsley, D. (2005) ‘The effect of network topology on the spread of epidemics’, Proceedings of the 24th IEEE Conference on Computer Communications (INFOCOM), Miami, FL, March, Vol. II, pp.1455–1466.
4. Jiang, A. and Bruck, J. (2005) ‘Monotone percolation and the topology control of wireless networks’, Proceedings of the 24th 1EEE Conference on Computer Communications (INFOCOM), Miami, FL, March, Vol. I, pp.327–338.
5. Karyotis, V.A. (2005) ‘A base case study of the worm propagation problem in the framework of topology control in wireless ad-hoc networks’, Master’s Thesis, School of Engineering & Applied Sciences, University of Pennsylvania, Philadelphia, PA, August.
6. Kephart, J.O. and White, S.R. (1991) ‘Directed-graph epidemiological models of computer viruses’, Proceedings of the Second 1EEE Computer Society Symposium on Research in Security and Privacy, May, pp.343–359.
7. Kephart, J.O. and White, S.R. (1993) ‘Measuring and modeling computer virus prevalence’, Proceedings of the Fourth IEEE Computer Society Symposium on Research in Security and Privacy, May, pp.2–15.
8. Le Boudec, J-Y. and Vojnovic, M. (2005) ‘Perfect simulation and stationarity of a class of mobility models’, Proceedings of the 24th 1EEE Conference on Computer Communications (INFOCOM), Miami, FL, March, Vol. IV, pp.2743–2754.
9. Liljeros, F., Edling, C.R. and Amaral, L.A.N. (2003) ‘Sexual networks: implications for the transmission of sexually transmitted infections’, Microbes and Infection, June, pp.189–196.
10. Pastor-Satorras, R. and Vespignani, A. (2002) ‘Epidemics and immunization in scale-free networks’, in S. Bornholdt and H. Schuster (Eds). Handbook of Graphs and Networks: From the Genome to the 1nternet, Berlin: Wiley-VCH, pp.113–132.
11. Pottie, G.J. and Kaiser, W.J. (2000) ‘Wireless integrated network sensors’, Communications of the ACM, Vol. 43, No. 5, pp.51–58.
12. Rappaport, T.S. (1996) Wireless Communications: Principles and Practice, Englewood Cliffs, NJ: Prentice-Hall, pp.69–122 and 139-196.
13. Rohloff, K.R. and Basar, T. (2005) ‘Stochastic behavior of random constant scanning worms’, Proceedings of the 14th 1nternational Conference on Computer Communications and Networks (1CCCN), October, San Diego, CA, pp.339–344.
14. Tanachaiwiwat, S. and Helmy, A. (2005) ‘VACCINE: war of the worms in wired and wireless networks’, Technical Report, University of Southern California, Los Angeles, USA, July.
15. Wang, Y., Chakrabarti, D., Wang, C. and Faloutsos, C. (2003) ‘Epidemic spreading in real networks: an eigenvalue approach’, Proceedings of the 22nd Symposium on Reliable Distributed Computing, Florence, Italy, October.
16. Wattenhofer, R., Li, L., Bahl, P. and Wang, Y-M. (2001) ‘Distributed topology control for power efficient operation in multihop wireless ad hoc networks’, Proceedings of 20th 1EEE Conference on Computer Communications (INFOCOM), Anchorage, AL, April, Vol. III, pp.1388–1397.
17. Zou, C.C., Gong, W. and Towsley, D. (2002) ‘Code red worm propagation modeling and analysis’, Proceedings of the Ninth ACM Conference on Computer and Communications (ACM CCS), Washington, DC, pp.138–147.
18. Zou, C.C., Gong, W. and Towsley, D. (2003) ‘Worm propagation modeling and analysis under dynamic quarantine defense’, First ACM Workshop on Rapid Malcode (WORM), Washington, DC.
19. Zou, C.C., Towsley, D. and Gong, W. (2004) ‘Email virus propagation modeling and analysis’, Technical Report TR-CSE-03-04, University of Massachusetts, Amherst, MA.
20. In addition, this justifies the fact that a malicious node usually has a higher probability to infect other network nodes compared to the infection capability of already infected network nodes.
21. Since the deployment region is fixed, the node density is proportional to the number of network nodes.