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基于等距映射( ISOMAP) 非线性降维算法, 提出了一种新的基于用户击键特征的用户身份认证算法, 该算法用测地距离代
替传统的欧氏距离, 作为样本向量之间的距离度量, 在用户击键特征向量空间中挖掘嵌入的低维黎曼流形, 进行用户识别。用采集
到的1 500 个击键模式数据进行实验测试, 结果表明, 该文的算法性能优于现有的同类算法, 其错误拒绝率( FRR) 和错误通过率
( FAR) 分别是1.65 和0 , 低于现有的同类算法。-Based isometric map (ISOMAP) non-linear dimensionality reduction algorithm, we propose a new feature based on the user' s keystrokes the user authentication algorithm with geodesic distance instead of the traditional Euclidean distance between the sample vector as distance measure, the feature vector space in the user' s keystrokes to mine low-Wei Liman embedded manifold, for user identification. 1 with the collected data for 500 Typing Mode experimental test results show that this algorithm outperforms existing similar algorithm, the false rejection rate (FRR) and error through rate (FAR) is 1.65 , respectively, and 0 , lower than existing similar algorithms.
替传统的欧氏距离, 作为样本向量之间的距离度量, 在用户击键特征向量空间中挖掘嵌入的低维黎曼流形, 进行用户识别。用采集
到的1 500 个击键模式数据进行实验测试, 结果表明, 该文的算法性能优于现有的同类算法, 其错误拒绝率( FRR) 和错误通过率
( FAR) 分别是1.65 和0 , 低于现有的同类算法。-Based isometric map (ISOMAP) non-linear dimensionality reduction algorithm, we propose a new feature based on the user' s keystrokes the user authentication algorithm with geodesic distance instead of the traditional Euclidean distance between the sample vector as distance measure, the feature vector space in the user' s keystrokes to mine low-Wei Liman embedded manifold, for user identification. 1 with the collected data for 500 Typing Mode experimental test results show that this algorithm outperforms existing similar algorithm, the false rejection rate (FRR) and error through rate (FAR) is 1.65 , respectively, and 0 , lower than existing similar algorithms.
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基于流形学习的用户身份认证.pdf
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