matlab中的gompertz代码-MAP-attack:最大先验(MAP)估计攻击matlab代码

上传者: 38712908 | 上传时间: 2023-03-25 13:36:26 | 文件大小: 1.11MB | 文件类型: ZIP
matlab中的gompertz代码介绍: 随机多方扰动 (RMP) 允许每个参与者通过非线性函数传递数据并使用参与者特定的随机矩阵将数据投影到较低维度来扰乱他/她的表格数据。 我们基于随机化的方案在两个阶段扰乱数据:第一个非线性阶段阻止贝叶斯估计攻击,而第二个线性阶段阻止独立分量分析攻击。 对于非线性扰动阶段,提出了一种新的非线性函数,称为“重复 Gompertz”函数。 该函数旨在调节受扰数据的 pdf,以保护异常和正常数据记录。 我们的方案是根据其对最大先验(MAP)估计攻击的恢复抵抗力来评估的。 对于异常检测,使用了堆叠去噪自编码器 (DAE)。 自编码器的超参数是根据验证集的最佳性能设置的。 每个数据集中的特征值被归一化为 [0, 1] 并与 5% 的异常记录合并,这些异常记录分布在 [0, 0.05] 或 [0.95, 1] 之间。 异常由自动编码器根据训练记录的输入和输出之间的平均绝对误差 (MAE) 进行识别。 根据三西格玛规则,一种众所周知的异常检测措施,重建误差预计为高斯分布,因此99.73%的误差值预计在阈值\mu(e) + 3\sigma(e )。 大于阈值的错

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