Optimal Wireless Smart Grid Networks Using Duo Attack Strategy
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How to Cite

Smys, S., and Haoxiang Wang. 2020. “Optimal Wireless Smart Grid Networks Using Duo Attack Strategy”. Journal of Electrical Engineering and Automation 2 (2): 60-67. https://doi.org/10.36548/jeea.2020.2.001.

Keywords

— Cognitive Radio Network
— Wireless Smart Grid Networks
— Spoofing
— Jamming
Published: 10-05-2020

Abstract

The Smart Grid Network (SGN) is one of the fastest developing technology and has been widely used because of its high performance, in power governance system and current power supply industry. The restriction over wired infrastructure has been overcome because of Wireless Smart Grid Networks (WSGN) which offers the best solution for power management. The most commonly used wireless networking approaches used is the Cognitive Radio Network (CRN). However, when the WSGN approach used is CRN, there is a lot of concern over communication security. The major attaches faced are fended using spoofing and hamming in CRN. The proposed work using optimal power distribution in order to fence off spoofing and jamming known as Maximum Attacking Strategy. Both jamming and spoofing will be able to interfere with many signal channels in order to ensure proper functioning of the channels. The attack strategy proposed in our work uses Duo-Attack using Jamming and Spoofing to evaluate the experiment and record the observations.

References

  1. B. Fateh, M. Govindarasu, and V. Ajjarapu. Wireless network design for transmission line monitoring in smart grid. IEEE Transactions on Smart Grid, 4(2):1076–1086, 2013.
  2. J. Huang, H. Wang, Y. Qian, and C. Wang. Priority-based traffic scheduling and utility optimization for cognitive radio communication infrastructure-based smart grid. IEEE Trans. on SG, 4(1):78–86, 2013.
  3. Z. Zhang, S. Gong, A. Dimitrovski, and H. Li. Time synchronization attack in smart grid: Impact and analysis. IEEE Transactions on Smart Grid, 4(1):87–98, 2013.
  4. Q. Peng, P. Cosman, and L. Milstein. Tradeoff between spoofing and jamming a cognitive radio. In Conference Record of the Forty-Third Asilomar Conference on Signals, Systems and Computers, pages 25– 29, Pacific Grove, California, 2009. IEEE.
  5. K. Gai, L. Qiu, M. Chen, H. Zhao, and M. Qiu. SA-EAST: securityaware efficient data transmission for ITS in mobile heterogeneous cloud computing. ACM Transactions on Embedded Computing Systems, 16(2):60, 2017.
  6. Y. Fan, Z. Zhang, M. Trinkle, A. Dimitrovski, J. Song, and H. Li. A cross-layer defense mechanism against GPS spoofing attacks on PMUs in smart grids. IEEE Trans. on SG, 6(6):2659–2668, 2015.
  7. Y. Wang, T. Gamage, and C. Hauser. Security implications of transport layer protocols in power grid synchrophasor data communication. IEEE Transactions on Smart Grid, 7(2):807–816, 2016.
  8. K. Gai, M. Qiu, H. Zhao, and J. Xiong. Privacy-aware adaptive data encryption strategy of big data in cloud computing. In 3rd Int’l Conf. on Cyber Sec. and Cloud Computing, pages 273–278. IEEE, 2016.
  9. L. Xiao, J. Liu, Q. Li, N. Mandayam, and V. Poor. User-centric view of jamming games in cognitive radio networks. IEEE Transactions on Information Forensics and Security, 10(12):2578–2590, 2015.
  10. J. Ma, Y. Liu, L. Song, and Z. Han. Multiact dynamic game strategy for jamming attack in electricity market. IEEE Transactions on Smart Grid, 6(5):2273–2282, 2015.
  11. H. Liu, H. Ning, Y. Zhang, Q. Xiong, and L. Yang. Role-dependent privacy preservation for secure V2G networks in the smart grid. IEEE Trans. on Information Forensics and Security, 9(2):208–220, 2014.
  12. N. Zhang, N. Lu, N. Cheng, J. Mark, and X. Shen. Cooperative spectrum access towards secure information transfer for CRNs. IEEE J. on Selected Areas in Comm., 31(11):2453–2464, 2013.
  13. M. Pei, A. Swindlehurst, D. Ma, and J. Wei. Adaptive limited feedback for MISO wiretap channels with cooperative jamming. IEEE Transactions on Signal Processing, 62(4):993–1004, 2014.