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Systems, Methods, and Apparatuses for Implementing a Privacy-Preserving Social Media Data Outsourcing Model

机译:用于实现保护隐私的社交媒体数据外包模型的系统,方法和设备

摘要

In accordance with embodiments disclosed herein, there are provided methods and systems for implementing a privacy-preserving social media data outsourcing model. For example, there is disclosed a Data Services Provider (DSP) Framework system, which includes a receive interface to receive an unperturbed social media data set having social media data corresponding to each of a plurality of users represented therein; a data privacy engine to map the received unperturbed social media data set into a high-dimensional user-keyword matrix connecting each of the plurality of users represented with multi-variable keywords corresponding to each user's social media data within the unperturbed social media data set; the data privacy engine further to inject controlled noise generate as output, a perturbed user-keyword matrix which protects each of the plurality of users' privacy during a statistical query against the perturbed user-keyword matrix having the social media data of the plurality of users embodied therein by preventing an attacker from (i) inferring whether a targeted user by the attacker is one of the plurality of users or (ii) inferring whether any record is associated with the targeted user. Other related embodiments are disclosed.
机译:根据本文公开的实施例,提供了用于实现保护隐私的社交媒体数据外包模型的方法和系统。例如,公开了一种数据服务提供商(DSP)框架系统,其包括接收接口,以接收具有与其中所表示的多个用户中的每个用户相对应的社交媒体数据的不打扰的社交媒体数据集;数据隐私引擎,用于将接收到的不受干扰的社交媒体数据集映射到高维用户关键字矩阵,该多维用户关键字矩阵连接用多变量关键字表示的多个用户中的每一个,该多变量关键字对应于不受干扰的社交媒体数据集内的每个用户的社交媒体数据;数据隐私引擎进一步注入受控噪声,作为受控噪声生成,以作为输出,以针对具有多个用户社交媒体数据的受干扰用户关键字矩阵在统计查询期间保护多个用户隐私中的每一个通过防止攻击者(i)推断攻击者的目标用户是否是多个用户之一或(ii)推断是否有任何记录与目标用户相关联,来体现在其中。公开了其他相关的实施例。

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