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論文筆記:ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learn
時間 2021-01-11
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這篇文章是上一篇Membership Inference Attacks Against Machine Learning Models的跟蹤研究,其提出了三個攻擊模型,將上一篇中的模型一步步簡化。 第一個攻擊模型是將上一篇中的影子模型數量降到一個,發現實驗效果不會有啥下降。 第二個模型放寬攻擊者對目標模型訓練集的限制,認爲攻擊者可以對其一無所知。影子模型的訓練集採用的是和目標模型不同領域的數據集
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相關文章
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論文筆記:Membership Inference Attacks Against Machine Learning Models
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論文解析:Membership Inference Attacks Against Machine Learning Models(一看即懂)
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