De-anonymiation method for networks based on DeepLink

Pei WANG; Yan JIA; Aiping LI; Qianyue JIANG

doi:10.11959/j.issn.2096-109x.2020045

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De-anonymiation method for networks based on DeepLink

Papers | 更新时间：2024-06-03

- De-anonymiation method for networks based on DeepLink
- Chinese Journal of Network and Information Security Vol. 6, Issue 4, Pages: 104-108(2020)
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- DOI：10.11959/j.issn.2096-109x.2020045
  CLC： TP183
- Online First：2020-08，
  
  Published：15 August 2020
- 稿件说明：
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Pei WANG, Yan JIA, Aiping LI, et al. De-anonymiation method for networks based on DeepLink[J]. Chinese Journal of Network and Information Security, 2020, 6(4): 104-108.
DOI：

Pei WANG, Yan JIA, Aiping LI, et al. De-anonymiation method for networks based on DeepLink[J]. Chinese Journal of Network and Information Security, 2020, 6(4): 104-108. DOI： 10.11959/j.issn.2096-109x.2020045.

摘要

现有的社交网络去匿名方法主要是基于网络结构，对网络结构进行学习与表示是去匿名的关键。用户身份链接（user identity linkage）的目的是检测来自不同社交网络平台的同一个用户。基于深度学习的跨社交网络用户对齐技术，很好地学习了不同社交网络的结构特征，实现了跨社交网络的用户对齐。将该技术用于同一社交网络匿名用户识别，实验结果优于传统去匿名方法。

Abstract

Existing de-anonymization technologies are mainly based on the network structure.To learn and express network structure is the key step of de-anonymization.The purpose of the user identity linkage is to detect the same user from different social networking platforms.DeepLink is a cross-social network user alignment technology.It learns the structural of the social networks and align anchor nodes through deep neural networks.DeepLink was used to identify de-anonymization social networks

and the results outperforms the traditional methods.

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references

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