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首页> 外文会议>European symposium on research in computer security;International workshop on cryptocurrencies and blockchain technology;International workshop on data privacy management >Graph Perturbation as Noise Graph Addition: A New Perspective for Graph Anonymization
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Graph Perturbation as Noise Graph Addition: A New Perspective for Graph Anonymization

机译：图摄动作为噪声图加法：图匿名化的新视角

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摘要

Different types of data privacy techniques have been applied to graphs and social networks. They have been used under different assumptions on intruders' knowledge, i.e., different assumptions on what can lead to disclosure. The analysis of different methods is also led by how data protection techniques influence the analysis of the data, i.e., information loss or data utility. One of the techniques proposed for graph is graph perturbation. Several algorithms have been proposed for this purpose. They proceed adding or removing edges, although some also consider adding and removing nodes. In this paper we propose the study of these graph perturbation techniques from a different perspective. Following the model of standard database perturbation as noise addition, we propose to study graph perturbation as noise graph addition. We think that changing the perspective of graph sanitization in this direction will permit to study the properties of perturbed graphs in a more systematic way.
机译：不同类型的数据隐私技术已应用于图表和社交网络。他们一直在对入侵者的知识，即，不同的假设不同的假设使用的是什么会导致泄露。不同的方法分析也由数据保护技术是如何影响数据，即，信息丢失或数据效用的分析领导。为图提出的一种技术是图扰动。为此已经提出了几种算法。他们将继续执行添加或删除边缘，尽管有些也可以考虑添加和删除节点。在本文中，我们提出的这些图摄技术从不同的角度研究。遵循标准数据库摄动作为噪声加法的模型，我们建议研究图摄动作为噪声图加法。我们认为，朝着这个方向改变图消毒的观点将允许以更系统的方式研究被扰动图的性质。

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