Journal of Guangxi Teachers Education University (Philosophy and Social Sciences Edition) ›› 2021, Vol. 39 ›› Issue (2): 21-31.doi: 10.16088/j.issn.1001-6600.2020082601

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A New Method for Invulnerability Analysis of Spatial Information Networks

ZHUO Ming1, LIU Leyuan1, ZHOU Shijie1*, YANG Peng1,2, WAN Simin2   

  1. 1. School of Information and Software Engineering, University of Science and Technology of China, Chengdu Sichuan 610054, China;
    2. School of Mathematical Sciences, University of Science and Technology of China, Chengdu Sichuan 611731, China
  • Received:2020-08-26 Revised:2020-09-22 Online:2021-03-25 Published:2021-04-15

Abstract: In next-generation networks, Spatial Information Networks (SINs) are expected to play an increasingly important role in providing Internet services over long distances and full coverage in an efficient manner. Most future networks will be hybrid-connecting nodes in space, near space, and on land through satellite links. Security is an essential concern in such networks since it is susceptible to a host of attacks, including eavesdropping, session hijacking, data corruption, and split attack. In this article, various security attacks that are possible in spatial information networks are addressed and different solutions proposed to existing invulnerability analysis in these networks are outlined. Setting in the split attack, a scheme is pointed out to evaluate network invulnerability based on the importance of the node in the complex network and graph convolutional networks classification nodes. Through experiments on the simple network and real spatial information networks, it is verified that the suggested approach has good discrimination and accuracy.

Key words: spatial nformation networks, node importance, graph convolutional networks, invulnerability

CLC Number: 

  • TP391
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