PriDe: A Quantitative Measure of Privacy-Loss in Interactive Querying Settings

Muhammad Imran Khan, S. Foley, B. O’Sullivan
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引用次数: 1

Abstract

This paper presents, PriDe, a model to measure the deviation of an analyst's (user) querying behaviour from normal querying behaviour. The deviation is measured in terms of privacy, that is to say, how much of the privacy loss has incurred due to this shift in querying behaviour. The shift is represented in terms of a score - a privacy-loss score, the higher the score the more the loss in privacy. Querying behaviour of analysts are modelled using n-grams of SQL query and subsequently, behavioural profiles are constructed. Profiles are then compared in terms of privacy resulting in a quantified score indicating the privacy loss.
骄傲:交互式查询设置中隐私损失的定量测量
本文提出了一个度量分析师(用户)查询行为与正常查询行为偏差的模型PriDe。这种偏差是根据隐私来衡量的,也就是说,由于查询行为的这种转变,造成了多少隐私损失。这种变化用一个分数来表示——隐私损失分数,分数越高,隐私损失越大。使用SQL查询的n-grams对分析师的查询行为进行建模,随后构建行为概况。然后比较配置文件的隐私性,得出一个量化的分数,表明隐私损失。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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