公开(公告)号：US20180097876A1

公开(公告)日：2018-04-05

申请号：US15282761

申请日：2016-09-30

Applicant: Hewlett Packard Enterprise Development LP

Inventor： Jerome Rolia ,  Martin Arlitt ,  Gowtham Bellala ,  Wei-Nchih Lee ,  Jose Alberto Cueto Barcenas ,  Sherif Abdelwahab

IPC: H04L29/08 ,  H04L12/24

CPC classification number: H04L67/1076 ,  H04L41/0816 ,  H04L41/0893 ,  H04L41/12 ,  H04L41/5025 ,  H04L41/5051 ,  H04L41/5096 ,  H04L67/1046

Abstract: Examples herein involve managing overlay networks of application components. In examples herein, application components may create overlay networks based on policies of the application components and an environment of the overlay network. The overlay network may be adjusted based on changes to the policies or the environment.

公开(公告)号：US20170053214A1

公开(公告)日：2017-02-23

申请号：US15307619

申请日：2014-04-28

Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP

Inventor： Gowtham Bellala ,  Jung Gun Lee ,  Wei Lu

IPC: G06N99/00 ,  G06N5/04 ,  H04L29/06

Abstract: Network flow classification can include clustering a network flow database into a number of at least one of applications and network flows. Network flow classification can include classifying the number of the at least one of applications and network flows.

Abstract translation: 网络流分类可以包括将网络流数据库聚类成多个应用和网络流中的至少一个。 网络流分类可以包括对应用和网络流中的至少一个的数量进行分类。

公开(公告)号：US20160217378A1

公开(公告)日：2016-07-28

申请号：US14914141

申请日：2013-08-30

Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP

Inventor： Gowtham Bellala ,  Manish Marwah ,  Martin Arlitt ,  Amip J. Shah

IPC: G06N5/04 ,  G06N99/00

CPC classification number: G06N5/04 ,  G05B15/02 ,  G05B23/024 ,  G06N20/00

Abstract: Described herein are techniques for identifying anomalous behavior of a monitored entity. Features can be extracted from data related to operation of an entity. The features can be mapped to a plurality of states to generate a state sequence. An observed value of a metric can be compared to an expected value of the metric based on the state sequence.

Abstract translation: 这里描述的是用于识别受监视实体的异常行为的技术。 可以从与实体的操作相关的数据中提取特征。 可以将特征映射到多个状态以生成状态序列。 可以将度量的观察值与基于状态序列的度量的期望值进行比较。