公开(公告)号：US11659026B2

公开(公告)日：2023-05-23

申请号：US16855305

申请日：2020-04-22

Applicant: VMware, Inc.

Inventor： Alok Tiagi ,  Farzad Ghannadian ,  Karen Hayrapetyan ,  Laxmikant Vithal Gunda ,  Sunitha Krishna ,  Ashot Aslanyan ,  Anirban Sengupta

IPC: H04L47/78 ,  H04L47/125 ,  G06K9/62 ,  H04L9/40 ,  H04L41/22 ,  H04L67/01

CPC classification number: H04L47/781 ,  G06K9/6257 ,  H04L41/22 ,  H04L47/125 ,  H04L63/20 ,  H04L67/01

Abstract: The disclosure provides an approach for workload labeling and identification of known or custom applications. Embodiments include determining a plurality of sets of features comprising a respective set of features for each respective workload of a first subset of a plurality of workloads. Embodiments include identifying a group of workloads based on similarities among the plurality of sets of features. Embodiments include receiving label data from a user comprising a label for the group of workloads. Embodiments include associating the label with each workload of the group of workloads to produce a training data set. Embodiments include using the training data set to train a model to output labels for input workloads. Embodiments include determining a label for a given workload of the plurality of workloads by inputting features of the given workload to the model.

公开(公告)号：US20230239204A1

公开(公告)日：2023-07-27

申请号：US17677039

申请日：2022-02-22

Applicant: VMware, Inc.

Inventor： Karen Hayrapetyan ,  Sunitha Krishna ,  Nikash Walia ,  Margaret Petrus

IPC: H04L41/0813 ,  H04L41/12 ,  H04L9/40

CPC classification number: H04L41/0813 ,  H04L41/12 ,  H04L63/104

Abstract: Systems and methods are described for recommending security groups using graph-based learning models. A server can create a network graph that illustrates network flows between devices in a network and security groups that the devices belong to. The network graph can include nodes that represent the devices and security groups. The server can apply a graph-based learning model to learn embeddings of the nodes and create vectors using the embeddings. Using vectors of two nodes, the server can calculate a vector that represents an edge between the two nodes. The server can apply a binary classifier determine whether the edge should exist. A “true” classification between two nodes can indicate that they should be able to communicate, and vice versa. A “true” classification between a device node and a security group node can indicate that the device should be assigned to the security group, and vice versa.

公开(公告)号：US11765179B2

公开(公告)日：2023-09-19

申请号：US17677039

申请日：2022-02-22

Applicant: VMware, Inc.

Inventor： Karen Hayrapetyan ,  Sunitha Krishna ,  Nikash Walia ,  Margaret Petrus

IPC: G06F15/177 ,  H04L41/0813 ,  H04L9/40 ,  H04L41/12

CPC classification number: H04L41/0813 ,  H04L41/12 ,  H04L63/104

Abstract: Systems and methods are described for recommending security groups using graph-based learning models. A server can create a network graph that illustrates network flows between devices in a network and security groups that the devices belong to. The network graph can include nodes that represent the devices and security groups. The server can apply a graph-based learning model to learn embeddings of the nodes and create vectors using the embeddings. Using vectors of two nodes, the server can calculate a vector that represents an edge between the two nodes. The server can apply a binary classifier determine whether the edge should exist. A “true” classification between two nodes can indicate that they should be able to communicate, and vice versa. A “true” classification between a device node and a security group node can indicate that the device should be assigned to the security group, and vice versa.

公开(公告)号：US20220398255A1

公开(公告)日：2022-12-15

申请号：US17837334

申请日：2022-06-10

Applicant: VMware, Inc.

Inventor： Anthony Fenzl ,  Vinith Podduturi ,  Kamalika Das ,  Karen Hayrapetyan ,  Margaret Petrus

IPC: G06F16/26 ,  G06F16/28 ,  H04L9/40

Abstract: Some embodiments provide a mechanism to automatically group workloads of a network into clusters of related workloads. The method of some embodiments displays consolidated workload data for a network. The method, for each of multiple workloads: (1) receives a set of identifiers characterizing the workload; and (2) converts the set of identifiers to a vector representation of the workload. The method then identifies clusters of workloads based on the vector representations of the workloads. The method then displays the workloads grouped in the identified clusters and displays data flows between the clusters of workloads. Converting the set of identifiers to a vector representation of the workload may include applying a similarity metric to the set of identifiers.

公开(公告)号：US20230239306A1

公开(公告)日：2023-07-27

申请号：US17582943

申请日：2022-01-24

Applicant: VMware, Inc.

Inventor： Karen Hayrapetyan ,  Sunitha Krishna ,  Nikash Walia ,  Margaret Petrus

IPC: H04L9/40 ,  G06N20/00 ,  G06F16/23

CPC classification number: H04L63/104 ,  G06N20/00 ,  G06F16/2365

Abstract: Systems and methods are described for recommending security groups using graph-based learning models. A server can create a network graph that illustrates network flows between devices in a network and security groups that the devices belong to. The network graph can include nodes that represent the devices and security groups. The server can apply a graph-based learning model to learn embeddings of the nodes and create vectors using the embeddings. Using vectors of two nodes, the server can calculate a vector that represents an edge between the two nodes. The server can apply a binary classifier determine whether the edge should exist. A “true” classification between two nodes can indicate that they should be able to communicate, and vice versa. A “true” classification between a device node and a security group node can indicate that the device should be assigned to the security group, and vice versa.