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A game-theoretic approach for channel security against active time-varying attacks based on artificial noise

  • Ling ChenEmail author
  • Mingchu Li
  • Ling Qin
  • Yingmo Jie
Original Research
  • 20 Downloads

Abstract

To penetrate sensitive communication systems, attackers can attack the channel using an active time-varying (ATV) way, which will lead to a great information loss. The conventional approach is to encrypt the original signal making it difficult for attackers to get information. However, this technology is constrained by the limited wireless terminal equipment. In this paper, we choose to insert artificial noise into the channel, which aims at disturbing the attackers and reducing the loss of the system once attacks occur. However, this technology would produce some side effects and there is a tradeoff between inserting artificial noise and minimizing information loss. In this paper, we deal with this issue and propose a game-theoretic framework to minimize the total losses. We model the problem as a Stackelberg security game between the attacker and the defender. Furthermore, we propose a novel method to reduce the searching space of computing the Strong Stackelberg Equilibrium which is the optimal defense strategy. This algorithm reduces a M-dimensional problem to M 1-dimensional problems so that the complexity is lowered. The experimental results show that our proposed algorithm significantly outperforms other non-strategic strategies in terms of decreasing the total losses against ATV attacks.

Keywords

Active time-varying attacks Artificial noise Stackelberg game Stackelberg equilibrium Channel security 

Notes

Acknowledgements

This paper is supported by Nature Science Foundation of China under Grant nos. 61572095, 61877007. An earlier version of this paper was presented at the 13th International Conference on Future Networks and Communications.

Compliance with ethical standards

Conflicts of interest

The authors declare that they have no conflict of interest.

Humans and animals participants

This article does not contain any studies with human participants or animals performed by any of the authors.

Informed consent

Informed consent was obtained from all individual participants included in the study.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.School of Mathematical SciencesDalian University of TechnologyDalianChina
  2. 2.School of Software TechnologyDalian University of TechnologyDalianChina
  3. 3.School of Mechanical EngineeringShanghai Jiaotong UniversityShanghaiChina

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