Propagation of Spurious Data for Wireless Cognitive Sensor Network in the Smart Grid: A Social Network Method

Abstract:

The nature of white space utilization, tremendous data processing, heterogeneous coexistence and security guarantees in Wireless Cognitive Sensor Network (WCSN) brings significant advantages over traditional Wireless Sensor Network (WSN) used in the smart grid. However, one of the main security threats to WCSN in the smart grid is the transmission of spurious data by malicious secondary users, which can induce the control center to make a wrong spectrum allocation and power dispatching decisions. In this paper, after analyzing the reference structure of smart grid and the feasibility of applying the epidemic theory into WCSN, we propose the UDG model of WCSN in the smart grid. Based on the epidemic theory in social network, we model and analyze the spurious data propagation process and identify key factors determining potential epidemic outbreaks in WCSN. In conclusion, we validate the feasibility of SIS model and perform investigations on the system dynamics.

• Periodical: Advanced Materials Research (Volumes 546-547)
• Pages: 242-247
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.546-547.242
• Online since: July 2012
• Authors: Wei Min Lang, Yuan Cheng Zhu, Hu Sheng Li
• Keywords: SIS Model, Smart Grid (SG), Social Network, Spurious Data Propagation, Wireless Cognitive Sensor Network

References

[1] A. Zaballos, A. Vallejo, J. M. Selga, Heterogeneous communication architecture for the smart grid, IEEE Network, vol. 25, no. 5, pp.30-37, May, (2011).

DOI: 10.1109/mnet.2011.6033033

[2] B. Heile, Smart grid for green communications, IEEE Wireless Commun. Magzine, vol. 17, pp.4-6, Jun., (2010).

[3] C. Gungor, B. Lu and G. P. Hancke, Opportunities and challenges of wireless sensor networks in smart grid, IEEE Trans. Ind. Electron., vol. 57, no. 10, pp.3557-3564, Oct., (2010).

DOI: 10.1109/tie.2009.2039455

[4] O. Akan, O. Karli, O. Ergul, Cognitive radio sensor networks, IEEE Network, vol. 23, pp.34-40, Apr. (2009).

DOI: 10.1109/mnet.2009.5191144

[5] S. Maleki, A. Pandharipande and G. Leus, Energy-efficient distributed spectrum sensing for cognitive sensor networks, IEEE Sensors Journal, vol. 11, pp.565-573, (2011).

DOI: 10.1109/jsen.2010.2051327

[6] M. E. J. Newman, Network: an introduction, Oxford University Press, New York, (2010).

[7] P. De, L. Yonghe, S. K. Das, An epidemic theoretic framework for vulnerability analysis of broadcast protocols in wireless sensor networks, IEEE Transactions on Mobile Computing, vol. 8, no. 3, pp.413-425, Mar. (2009).

DOI: 10.1109/tmc.2008.115

[8] R. Di Pietro, N. V. Verde, Introducing epidemic models for data survivability in Unattended Wireless Sensor Networks, in Proc. of 2011 IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks, Las Vegas, USA, Jun. 20-24, (2011).

DOI: 10.1109/wowmom.2011.5986165