Modeling Adversarial Behavior Against Mobility Data Privacy
Modeling Adversarial Behavior Against Mobility Data Privacy
复制标题
针对移动数据隐私的对抗行为建模
DOI：
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复制
发表时间：
2020
期刊：
影响因子：
--
通讯作者：
A. Monreale
中科院分区：
文献类型：
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作者：
Roberto Pellungrini;Luca Pappalardo;F. Simini;A. Monreale
隐私风险评估是任何隐私感知分析过程中的关键问题。传统的隐私风险评估框架系统地生成潜在对手的假设知识，评估风险，而不现实地模拟对手在执行攻击时使用的背景知识的集合。在这项工作中，我们提出了一种新的移动数据隐私风险评估的对抗行为模型--模拟隐私退火法。我们将对手的行为建模为移动轨迹，并引入了一种优化方法来根据移动数据集中代表的个人产生的隐私风险来寻找最有效的对手轨迹。我们使用模拟退火法来优化对手的移动，并模拟对移动数据的可能攻击。最后，我们在真实的人类移动数据上测试了该方法的有效性，结果表明该方法能够更真实地模拟对手的知识收集过程。
Privacy risk assessment is a crucial issue in any privacy-aware analysis process. Traditional frameworks for privacy risk assessment systematically generate the assumed knowledge for a potential adversary, evaluating the risk without realistically modelling the collection of the background knowledge used by the adversary when performing the attack. In this work, we propose Simulated Privacy Annealing (SPA), a new adversarial behavior model for privacy risk assessment in mobility data. We model the behavior of an adversary as a mobility trajectory and introduce an optimization approach to find the most effective adversary trajectory in terms of privacy risk produced for the individuals represented in a mobility data set. We use simulated annealing to optimize the movement of the adversary and simulate a possible attack on mobility data. We finally test the effectiveness of our approach on real human mobility data, showing that it can simulate the knowledge gathering process for an adversary in a more realistic way.
DOI：
10.18637/jss.v103.i04
发表时间：
2019-07
期刊：
J. Stat. Softw.
影响因子：
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作者：
Luca Pappalardo;F. Simini;Gianni Barlacchi;Roberto Pellungrini
通讯作者：
Luca Pappalardo;F. Simini;Gianni Barlacchi;Roberto Pellungrini
DOI：
10.3390/s16071013
发表时间：
2016-06-30
期刊：
Sensors (Basel, Switzerland)
影响因子：
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作者：
Amer H;Salman N;Hawes M;Chaqfeh M;Mihaylova L;Mayfield M
通讯作者：
Mayfield M