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A Distributed Strategy for Defensing Objective Function Attack in Large-scale Cognitive Networks

  • Conference paper
Intelligent Computation in Big Data Era (ICYCSEE 2015)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 503))

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Abstract

Most of existed strategies for defending OFA (Objective Function Attack)are centralized, only suitable for small-scale networks and stressed on the computation complexity and traffic load are usually neglected. In this paper, we pay more attentions on the OFA problem in large-scale cognitive networks, where the big data generated from the network must be considered and the traditional methods could be of helplessness. In this paper, we first analyze the interactive processes between attacker and defender in detail, and then a defense strategy for OFA based on differential game is proposed, abbreviated as DSDG. Secondly, the game saddle point and optimal defense strategy have proved to be existed simultaneously. Simulation results show that the proposed DSDG has a less influence on network performance and a lower rate of packet loss.More importantly, it can cope with the large range OFA effectively.

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Author information

Authors and Affiliations

  1. College of Computer Science and Technology, Harbin Engineering University, Harbin, 150001, China

    Guangsheng Feng, Junyu Lin, Huiqiang Wang, Xiaoyu Zhao & Hongwu Lv

  2. School of Computer and Information Engineering, Harbin University of Commerce, Harbin, 150028, China

    Qiao Zhao

Authors
  1. Guangsheng Feng
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  2. Junyu Lin
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  3. Huiqiang Wang
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  4. Xiaoyu Zhao
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  5. Hongwu Lv
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  6. Qiao Zhao
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Editor information

Editors and Affiliations

  1. Harbin Institute of Technology, Harbin, China

    Hongzhi Wang  & Wanxiang Che  & 

  2. School of Computer Science and Technology, Heilongjiang Institute of Technology, Harbin, China

    Haoliang Qi  & Zhongyuan Han  & 

  3. Northeast Forestry University, Harbin, China

    Zhaowen Qiu

  4. Heilongjiang Institute of Technology, Harbin, China

    Leilei Kong

  5. Harbin Engineering University, China

    Junyu Lin

  6. Zhongkeyunhai Company, Harbin, China

    Zeguang Lu

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© 2015 Springer-Verlag Berlin Heidelberg

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Feng, G., Lin, J., Wang, H., Zhao, X., Lv, H., Zhao, Q. (2015). A Distributed Strategy for Defensing Objective Function Attack in Large-scale Cognitive Networks. In: Wang, H., et al. Intelligent Computation in Big Data Era. ICYCSEE 2015. Communications in Computer and Information Science, vol 503. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-46248-5_2

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  • DOI: https://doi.org/10.1007/978-3-662-46248-5_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-46247-8

  • Online ISBN: 978-3-662-46248-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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