Modeling Node Compromise Spread in Wireless Sensor Networks Using Epidemic Theory

ABSTRACT

Motivated by recent surfacing viruses that can spread over the air interfaces, in this paper, we investigate the potential disastrous threat of node compromise spreading in wireless sensor networks. Originating from a single infected node, we assume such a compromise can propagate to other sensor nodes via communication and preestablished mutual trust. We focus on the possible epidemic breakout of such propagations where the whole network may fall victim to the attack. Based on epidemic theory, we model and analyze this spreading process and identify key factors determining potential outbreaks. In particular, we perform our study on random graphs precisely constructed according to the parameters of the network, such as distance, key sharing constrained communication and node recovery, thereby reflecting the true characteristics therein. The analytical results provide deep insights in designing potential defense strategies against this threat. Furthermore, through extensive simulations, we validate our model and perform investigations on the system dynamics.

References

1. {1} I. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci, "A Survey on sensor networks," IEEE Communications Magazine, vol. 40, no. 8, 2002.
2. {2} R. M. Anderson and R. M. May, "Infectious Diseases of Human: Dynamics and Control" (Oxford Univ. Press, Oxford, 1991).
3. {3} S. Staniford, V. Paxson, and N. Weaver. "How to Own the Internet in Your Spare Time". In 11th Usenix Security Symposium, San Francisco, August, 2002.
4. {4} C. Hartung, J. Balasalle, and R. Han, "Node Compromise in Sensor Networks: The Need for Secure Systems", Technical Report CUCS-990-05 (2005).
5. {5} H. Chan, V. D. Gligor, A. Perrig, G. Muralidharan, "On the Distribution and Revocation of Cryptographic Keys in Sensor Networks", IEEE Transactions on Dependable and Secure Computing 2005.
6. {6} A. Khelil, C. Becker, J. Tian, K. Rothermel, "An Epidemic Model for Information Diffusion in MANETs", MSWiM 2002, pages 54- 60.
7. {7} N. T. J. Bailey, "The Mathematical Theory of Infectious Diseases and its Applications". Hafner Press, New York (1975).
8. {8} M. E. J. Newman, "Spread of epidemic disease on networks", Phys. Rev. E, 66 (2002), art. no. 016128.
9. {9} C. Moore and M. E. J. Newman, "Epidemics and percolation in small-world networks". Phys. Rev. E 61, 5678-5682 (2000).
10. {10} P. Grassberger, "On the critical behavior of the general epidemic process and dynamic percolation", Math. Biosc. 63 (1983) 157.
11. {11} L. Eschenauer and V. D. Gligor. "A key-management scheme for distributed sensor networks", in Proc. of the 9th Computer Communication Security - CCS'02, pages 41-47, Washington D.C., USA, November 2002.
12. {12} H. Chan, A. Perrig, and D. Song, "Random key predistribution schemes for sensor networks", in Proc. of the IEEE Symposium on Research in Security and Privacy - SP '03, pages 197-215, Washington D.C., USA, May 2003.
13. {13} Donggang Liu and Peng Ning, "Establishing pairwise keys in distributed sensor networks", in Proc. of the 10th ACM Conference on Computer and Communications Security - CCS '03, pages 52- 61, Washington D.C., USA, October 2003.
14. {14} H. Chan; V. D. Gligor, A. Perrig, G. Muralidharan, "On the Distribution and Revocation of Cryptographic Keys in Sensor Networks", IEEE Transactions on Dependable and Secure Computing, Volume 2, Issue 3, July-Sept. 2005.
15. {15} A. Chadha, Y. Liu. and S. Das, "Group key distribution via local collaboration in wireless sensor networks," in Proceedings of the IEEE SECON 2005, Santa Clara, CA, Sept. 2005.

Index Terms

• Computer systems organization

  • Dependable and fault-tolerant systems and networks

• General and reference

  • Cross-computing tools and techniques

    • Performance

• Hardware

  • Communication hardware, interfaces and storage

    • Signal processing systems

• Networks

  • Network performance evaluation

  • Network types

    • Mobile networks

    • Wireless access networks