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公开(公告)号：US08544087B1
公开(公告)日：2013-09-24
申请号：US12022425
申请日：2008-01-30
CPC分类号： H04L41/06 , G06F21/552 , H04L41/142 , H04L63/1416
摘要： A method for unsupervised anomaly detection, which are algorithms that are designed to process unlabeled data. Data elements are mapped to a feature space which is typically a vector space . Anomalies are detected by determining which points lies in sparse regions of the feature space. Two feature maps are used for mapping data elements to a feature apace. A first map is a data-dependent normalization feature map which we apply to network connections. A second feature map is a spectrum kernel which we apply to system call traces.
摘要翻译： 一种用于无监督异常检测的方法，它们是用于处理未标记数据的算法。 数据元素被映射到通常是向量空间的特征空间。 通过确定哪些点位于特征空间的稀疏区域来检测异常。 两个特征图用于将数据元素映射到特征空间。 第一张地图是我们适用于网络连接的依赖于数据的规范化特征图。 第二个特征图是我们应用于系统调用轨迹的频谱内核。
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2.发明申请公开(公告)号：US20150058982A1
公开(公告)日：2015-02-26
申请号：US13987690
申请日：2013-08-20
IPC分类号： H04L29/06
CPC分类号： H04L63/1425 , G06F17/30914
摘要： A method for unsupervised anomaly detection, which are algorithms that are designed to process unlabeled data. Data elements are mapped to a feature space which is typically a vector space d. Anomalies are detected by determining which points lies in sparse regions of the feature space. Two feature maps are used for mapping data elements to a feature apace. A first map is a data-dependent normalization feature map which we apply to network connections. A second feature map is a spectrum kernel which we apply to system call traces.
摘要翻译： 一种用于无监督异常检测的方法，它们是用于处理未标记数据的算法。 数据元素被映射到通常是向量空间d的特征空间。 通过确定哪些点位于特征空间的稀疏区域来检测异常。 两个特征图用于将数据元素映射到特征空间。 第一张地图是我们适用于网络连接的依赖于数据的规范化特征图。 第二个特征图是我们应用于系统调用轨迹的频谱内核。
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