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Topology Self-optimization for Anti-tracking Network via Nodes Distributed Computing

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Collaborative Computing: Networking, Applications and Worksharing (CollaborateCom 2021)

Abstract

Anti-tracking network aims to protect the privacy of network users’ identities and communication relationship. The research of P2P-based anti-tracking network has attracted more and more attentions because of its decentralization, scalability, and widespread distribution. But, P2P-based anti-tracking network still faces the attacks on network structure which can destroy the usability of anti-tracking network effectively. So, a secure and resilient network structure is an important prerequisite to maintain the stability and security of anti-tracking network. In this paper, we propose a topology self-optimization method for anti-tracking network via nodes distributed computing. Based on convex-polytope topology (CPT), our proposal achieves topology self-optimization by each node optimizing its local topology in optimum structure. Through the collaboration of all nodes in network, the whole network topology will evolve into the optimum structure. Our experimental results show that the topology self-optimization method improves the network robustness and resilience of anti-tracking network when confronting to the dynamic network environment.

Supported by the National Key Research and Development Program of China under Grant No. 2019YFB1005203, the National Natural Science Foundation of China under Grant No. U1736218.

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Acknowledgements

The authors would like to thank the anonymous reviewers for their insightful comments and suggestions on this paper. This work was supported in part by the National Key Research and Development Program of China under Grant No. 2019YFB1005203, the National Natural Science Foundation of China under Grant No. U1736218.

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Authors and Affiliations

  1. Institute of Information Engineering, Chinese Academy of Sciences, Bei**g, 100093, China

    Changbo Tian, Yongzheng Zhang & Tao Yin

  2. School of Cyber Security, University of Chinese Academy of Sciences, Bei**g, 100049, China

    Changbo Tian, Yongzheng Zhang & Tao Yin

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  1. Changbo Tian
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  2. Yongzheng Zhang
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Correspondence to Tao Yin .

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Editors and Affiliations

  1. Shanghai University, Shanghai, China

    Honghao Gao

  2. **’an Jiaotong-Liverpool University, Suzhou, China

    **nheng Wang

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Tian, C., Zhang, Y., Yin, T. (2021). Topology Self-optimization for Anti-tracking Network via Nodes Distributed Computing. In: Gao, H., Wang, X. (eds) Collaborative Computing: Networking, Applications and Worksharing. CollaborateCom 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 406. Springer, Cham. https://doi.org/10.1007/978-3-030-92635-9_24

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  • DOI: https://doi.org/10.1007/978-3-030-92635-9_24

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