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- W2945152172 abstract "Most, if not all, existing attribute inference attacks leverage users’ social friendship information and/or social behavioral information to infer the attributes of a target user. In this paper, we study this problem in a novel angle. Specifically, we study whether a user’s private attributes (e.g., age, gender, and education) can be inferred based on his or her query history, which is the first such attempt to the best of our knowledge. We present a thorough description of our query-based attribute inference attack and experimentally evaluate our method on a real-world dataset provided by Sogou. Experimental results show that our method can achieve 70.21% for the precision, 68.82% for the recall, and 69.50% for the F1-score on average. When predicting users’ gender, the proposed method has precision of 84.56%. This suggests that query records indeed disclose a significant amount of information about users." @default.
- W2945152172 created "2019-05-29" @default.
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- W2945152172 date "2019-04-17" @default.
- W2945152172 modified "2023-09-28" @default.
- W2945152172 title "You Are What You Search: Attribute Inference Attacks Through Web Search Queries" @default.
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- W2945152172 doi "https://doi.org/10.1007/978-3-030-16946-6_27" @default.
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