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公开(公告)号：US11122065B2
公开(公告)日：2021-09-14
申请号：US16103108
申请日：2018-08-14
Applicant: VMware, Inc.
Inventor： Bin Zan , Dexiang Wang , Zhen Mo , Vijay Ganti
Abstract: Feature vectors are abstracted from data describing application processes. The feature vectors are grouped to define non-anomalous clusters of feature vectors corresponding to normal application behavior. Subsequent feature vectors are considered anomalous if they do not fall within one of the non-anomalous clusters; alerts are issued for anomalous feature vectors. In addition, the subsequent feature vectors may be used to regroup feature vectors to adapt to changes in what constitutes normal application behavior.
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公开(公告)号：US20210027121A1
公开(公告)日：2021-01-28
申请号：US16518808
申请日：2019-07-22
Applicant: VMware, Inc.
Inventor： Bin Zan , Zhen Mo , Vamsi Akkineni , Vijay Ganti
Abstract: Machine learning-based techniques for representing computing processes as vectors are provided. In one set of embodiments, a computer system can receive a name of a computing process and context information pertaining to the computing process. The computer system can further train a neural network based on the name and the context information, where the training results in determination of weight values for one or more hidden layers of the neural network. The computer system can then generate, based on the weight values, a vector representation of the computing process that encodes the context information and can perform one or more analyses using the vector representation.
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