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Evaluation of a query-obfuscation mechanism for the privacy protection of user profile

机译:评估用户配置文件隐私保护的查询 - 混淆机制

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摘要

Traces related to our identity are left every day while we browse the Internet. Being the user’s information a very valued asset for most of the companies, user activities on Internet are permanently monitored, and the information obtained from this process is used by big advertising companies. Accurate user profiles are built based on web searches, tags, tweets and even clicks issued by users. Collecting and processing this huge amount of personal data represents a serious risk for the user’s privacy but most of people are not aware of such risk.\ud\udWe describe in this paper a way to measure the effectiveness of a query obfuscation method. Since privacy level of user profiles is only estimated theoretically in some previous work, we firstly create a privacy risk measuring tool in a Firefox add-on which we named PrivMeter. Besides warning the user about his privacy levels, this tool is especially useful to evaluate the obfuscation mechanism offered by another very well-known add-on called TrackMeNot. We find that, for identification attacks, TrackMeNot importantly improved the user’s privacy. However, against more sophisticated attacks, such as classification attacks, the obfuscation mechanism was not successful enough.
机译:我们每天浏览互联网时都会留下与我们身份有关的痕迹。作为用户信息,对于大多数公司而言,这是非常宝贵的资产,因此,Internet上的用户活动将受到永久监控,并且从此过程中获得的信息将由大型广告公司使用。准确的用户个人资料是根据用户的网络搜索,标签,推文甚至点击次数构建的。收集和处理如此大量的个人数据对用户的隐私构成了严重的风险,但是大多数人并未意识到这种风险。\ ud \ ud我们在本文中描述了一种测量查询混淆方法有效性的方法。由于用户配置文件的隐私级别只是理论上在以前的工作中估算的,因此我们首先在名为PrivMeter的Firefox附件中创建了隐私风险衡量工具。除了警告用户有关其隐私级别的信息外,该工具对于评估另一个非常著名的插件TrackMeNot所提供的混淆机制尤其有用。我们发现,对于身份识别攻击,TrackMeNot重要地改善了用户的隐私。但是,对于更复杂的攻击(例如分类攻击),混淆机制不够成功。

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