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Vulnerability Variants and Path Factors in Networks

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Machine Learning for Cyber Security (ML4CS 2020)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 12487))

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Abstract

The vulnerability of the network is one of the core contents of network security research, and there are several variables to test the network vulnerability from the perspective of network structure. For example, toughness, isolated toughness and their variants are defined from graph theory point of view, and these parameters works during the design phase to test the firmness of network. This paper studies the relationship between the existence of path factor and some variants which connect with vulnerability of networks. Moreover, we show that some of bounds of these variants are sharp.

Supported by Modern Education Technology Research Project in Jiangsu Province (No. 2019-R-75637) and Design of equipment access system based on 3D printing cloud service platform (No. 2019530101000686).

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Acknowledgments

We thank the reviewers for their constructive comments in improving the quality of this paper.

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Authors and Affiliations

  1. School of Computer Engineering, Jiangsu University of Technology, Changzhou, 213001, China

    Linli Zhu

  2. Department of Mathematics and Science Education, Faculty of Education, Harran University, Sanliurfa, Turkey

    Haci Mehmet Baskonus & Wei Gao

Authors
  1. Linli Zhu
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  2. Haci Mehmet Baskonus
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  3. Wei Gao
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Corresponding author

Correspondence to Linli Zhu .

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Editors and Affiliations

  1. Xidian University, Xi'an, China

    Xiaofeng Chen

  2. Guangzhou University, Guangzhou, China

    Hongyang Yan

  3. Michigan State University, East Lansing, MI, USA

    Qiben Yan

  4. Division of Computer, Electrical and Mathematical Sciences and Engineering, King Abdullah University of Science, Thuwal, Saudi Arabia

    Xiangliang Zhang

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Zhu, L., Baskonus, H.M., Gao, W. (2020). Vulnerability Variants and Path Factors in Networks. In: Chen, X., Yan, H., Yan, Q., Zhang, X. (eds) Machine Learning for Cyber Security. ML4CS 2020. Lecture Notes in Computer Science(), vol 12487. Springer, Cham. https://doi.org/10.1007/978-3-030-62460-6_1

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  • DOI: https://doi.org/10.1007/978-3-030-62460-6_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-62459-0

  • Online ISBN: 978-3-030-62460-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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