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A Network Coding Against Wiretapping Attacks of the Physical Layer Security Based on LDPC Code

  • Yujie Zheng
  • Jingqi Fu
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 924)

Abstract

The secure transmission of wireless network information has received wide attention. To solve Hacking threat problems that exist in the wireless network, this paper presented a construction method which is based on the classic Low-Density Parity-Check (LDPC) encoding method, the transmission model of the physical security was studied, and the safe transmission scheme was developed under the gaussian eavesdropping channel, the code with a nested structure was designed, and the random selection of code words was determined, message processing is carried out through an improved large-column weight and low complexity check matrix, not only effectively reduce the requirement for storage space and the complexity of the information processing, but also effectively decrease the error rate of the system. Simulation experiments and comparative analysis show that the bit error rate (BER) of the encoding method in this paper is significantly lower than that of Progressive Edge Growth (PEG) algorithm, which achieves the anti-eavesdropping effect.

Keywords

LDPC Physical layer security Network coding Eavesdropping 

Notes

Acknowledgments

This work was financially supported by the Science and Technology Commission of Shanghai Municipality of China under Grant (No. 17511107002).

References

  1. 1.
    Shannon, C.E.: Communication theory of secrecy systems.In: International Conference on Autonomous Agents and Multiagent Systems. International Foundation for Autonomous Agents and Multiagent Systems, pp.1951–1952 (2015)Google Scholar
  2. 2.
    Wyner, A.D.: The wire-tap channel. Bell Labs Tech. J. 54(8), 1355–1387 (2014)MathSciNetCrossRefGoogle Scholar
  3. 3.
    Csiszar, I., Korner, J.: Broadcast channels with confidential messages. IEEE Trans. Inf. Theory 24(3), 339–348 (2003)MathSciNetCrossRefGoogle Scholar
  4. 4.
    Zhang, S., Liew, S.C., Lam, P.P.: Hot topic: physical-layer network coding. In: International Conference on Mobile Computing and Networking, MOBICOM 2006, Los Angeles, Ca, USA, pp. 358–365, September 2006Google Scholar
  5. 5.
    Ahlswede, R., Cai, N., Li, S.Y.R., et al.: Network information flow. IEEE Trans. Inf. Theory 46(4), 1204–1216 (2002)MathSciNetCrossRefGoogle Scholar
  6. 6.
    Cai, N., Yeung, R.W.: Secure network coding. In: 2002 Proceedings of the IEEE International Symposium on Information Theory, p. 323. IEEE (2008)Google Scholar
  7. 7.
    Wang, J., Wang, W.: Probability Theory and Mathematical Statistics. Advanced Education Press, Beijing (2015)Google Scholar
  8. 8.
    Mahdavifar, H., Vardy, A.: Achieving the secrecy capacity of wiretap channels using polar codes. IEEE Trans. Inf. Theory 57(10), 6428–6443 (2011)MathSciNetCrossRefGoogle Scholar
  9. 9.
    Dorf, R., Simon, M., Milstein, L., et al.: Digital communication. IEEE Trans. Acoust. Speech Signal Process. 32(1), 190 (2017)Google Scholar
  10. 10.
    Liu, L., Yan, Y., Ling, C.: Achieving secrecy capacity of the gaussian wiretap channel with polar lattices. IEEE Trans. Inf. Theory 64(3), 1647–1665 (2018)MathSciNetCrossRefGoogle Scholar
  11. 11.
    Hu, X.Y., Eleftheriou, E., Arnold, D.M.: Regular and irregular progressive edge-growth tanner graphs. IEEE Trans. Inf. Theory 51(1), 386–398 (2005)MathSciNetCrossRefGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  • Yujie Zheng
    • 1
  • Jingqi Fu
    • 1
  1. 1.Department of Automation, College of Mechatronics Engineering and AutomationShanghai UniversityShanghaiChina

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