公开(公告)号：US20200304393A1

公开(公告)日：2020-09-24

申请号：US16357873

申请日：2019-03-19

Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP

Inventor： Rangaprasad SAMPATH ,  Madhusoodhana Chari SESHA ,  Srinidhi Hari PRASAD

IPC: H04L12/26 ,  H04L12/24 ,  G06N20/00

Abstract: A device may track network traffic and may determine sample points associated with a plurality of time intervals, where each sample point from the plurality of sample points that is associated with a respective time interval from the plurality of time intervals comprises a count of packet lengths associated with a plurality of packets that comprise at least a specified portion of total network volume for the respective time interval and a total number of packet lengths observed during the respective time interval. The device may generate a plurality of clusters of the plurality of sample points and may, in response to determining a plurality of new sample points associated with a plurality of new time intervals based on the network traffic, determine a network traffic trend for the network based at least in part on a distribution of the plurality of new sample points within the plurality of clusters.

公开(公告)号：US20220327330A1

公开(公告)日：2022-10-13

申请号：US17406792

申请日：2021-08-19

Applicant: Hewlett Packard Enterprise Development LP

Inventor： Madhusoodhana Chari SESHA ,  A Abdul SAMADH ,  Jayanth ANANTHAPADMANABAN ,  Sai Ram GANNA ,  Krishna Mohan ELLURU

IPC: G06K9/62 ,  H04L12/26 ,  G06N3/08 ,  G06N5/00

Abstract: A system and a method of classifying data and providing an accuracy of classification are described. The method includes determining values of statistical features associated with data packets present in a data stream. The values of statistical features are provided to a data model for producing a classification output including the data packets classified into one or more categories. While producing the classification output, the data model extracts heuristics for each of the values of statistical features, compares the heuristics with one or more conditional checks defined at each node within the data model, and determines a cumulative score based on results of the comparing. The cumulative score is determined by aggregating a score assigned to successful clearance of each conditional check. The cumulative score indicates an accuracy of the classification output.

公开(公告)号：US20200304386A1

公开(公告)日：2020-09-24

申请号：US16358084

申请日：2019-03-19

Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP

Inventor： Rangaprasad SAMPATH ,  Madhusoodhana Chari SESHA ,  Parikshit MISRA

IPC: H04L12/26 ,  G06N20/00 ,  G06N5/00

Abstract: A device may determine sample points associated with network routes within a network during a time interval, wherein each sample point that is associated with a respective network route comprises an amount of uptime for the respective network route during the time interval and a total frequency of state changes for the respective network route during the time interval. The device may generate, using an unsupervised machine learning mechanism, clusters of the sample points and may label the network routes with route stability labels based at least in part on the clusters. The device may generate, using a supervised machine learning mechanism, a route stability classifier based at least in part on the route stability labels for the network routes, and may determine, using the route stability classifier, a route stability of a new network route within the network.

公开(公告)号：US20210400067A1

公开(公告)日：2021-12-23

申请号：US17225873

申请日：2021-04-08

Applicant: Hewlett Packard Enterprise Development LP

Inventor： Priyanka Chandrashekar BHAT ,  Madhusoodhana Chari SESHA ,  Rashmi VEDI

IPC: H04L29/06 ,  G06K9/62 ,  G06N20/00

Abstract: Examples include detection of unclassified traffic in a network. Some examples use an unsupervised machine learning mechanism for generating a first set of clusters of a first set of samples associated with a first set of time intervals, based at least in part on network traffic over a network, in a first predetermined period of time. Each sample associated with the respective time interval includes distribution of packets based on their packet lengths. In response to retrieving a second set of samples associated with a second set of time intervals, based at least in part on network traffic, a second set of clusters of the second set of samples is generated. It is determined whether one or more features of the second set of clusters vary as compared to one or more features of the first set of clusters of the first set of samples to detect unclassified traffic in the second set of samples.

公开(公告)号：US20210168083A1

公开(公告)日：2021-06-03

申请号：US17085528

申请日：2020-10-30

Applicant: Hewlett Packard Enterprise Development LP

Inventor： Tamil Esai SOMU ,  Srinidhi HARI PRASAD ,  Madhusoodhana Chari SESHA

IPC: H04L12/851 ,  H04L12/26

Abstract: Systems and methods are provided for a light-weight model for traffic classification within a network fabric. A classification model is deployed onto an edge switch within a network fabric, the model enabling traffic classification using a set of statistical features derived from packet length information extracted from the IP header for a plurality of data packets within a received traffic flow. The statistical features comprise a number of unique packet lengths, a minimum packet length, a maximum packet length, a mean packet length, a standard deviation of the packet length, a maximum run length, a minimum run length, a mean run length, and a standard deviation of run length. Based on the calculated values for the statistical features, the edge switch determines a traffic class for the received traffic flow and tags the traffic flow with an indication of the determined traffic class.

公开(公告)号：US20240259034A1

公开(公告)日：2024-08-01

申请号：US18160063

申请日：2023-01-26

Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP

Inventor： MANTEJ SINGH GILL ,  Dhamodhran SATHYANARAYANAMURTHY ,  Madhusoodhana Chari SESHA ,  Anil BABULAL

IPC: H03M7/30

CPC classification number: H03M7/6011 ,  H03M7/3073

Abstract: Systems and methods are provided for compressing a time-series dataset from a monitored device into a compressed dataset representation. Using an unsupervised machine learning model, the system may group a contiguous set of datapoints of the time-series dataset and group, using a distance algorithm, the first cluster to a first motif. A compressed dataset representation can be generated using a plurality of motifs, including the first motif, that is stored in place of the time-series dataset. This can allow the time-series dataset to be replaced with the compressed dataset representation, illustrating an overall, abstracted definition of the time-series dataset rather than the individual data points.

公开(公告)号：US20230049886A1

公开(公告)日：2023-02-16

申请号：US17403213

申请日：2021-08-16

Applicant: Hewlett Packard Enterprise Development LP

Inventor： Madhusoodhana Chari SESHA ,  Ramasamy APATHOTHARANAN ,  Shree Phani Sundara BANAVATHI NARAYANA SASTRY ,  Priyanka Chandrashekar BHAT ,  Venkatesh MADI ,  Srinidhi HARI PRASAD ,  Azath Abdul SAMADH ,  Kumar SURESH ,  Manjunath Rajendra BATAKURKI ,  Madhumitha RAJAMOHAN ,  Ganesh PAGOTI ,  Sriram MAHADEVA ,  Karthik ARUMUGAM ,  Harish RAMACHANDRAN ,  Fahad KAMEEZ

IPC: H04L29/06 ,  G06K9/62 ,  G06N20/00

Abstract: Some examples relate to classifying IoT malware at a network device. An example includes receiving, by a network device, network traffic from an Internet of Things (IoT) device. Network device may analyze network parameters from the network traffic with a machine learning model. In response to analyzing, network device may classify the network traffic into a category of malware activity. Network device may determine an effectiveness of network traffic classification by measuring a deviation of the network parameters from previously trained network parameters that were used for training the machine learning model. In response to a determination that the deviation of the network parameters from the trained network parameters is more than a pre-defined threshold, network device may generate an alert highlighting the deviation, which allows a user to perform a remedial action pertaining to the IoT device.

公开(公告)号：US20220158918A1

公开(公告)日：2022-05-19

申请号：US17406837

申请日：2021-08-19

Applicant: Hewlett Packard Enterprise Development LP

Inventor： Madhusoodhana Chari SESHA ,  Ankit Kumar SINHA ,  Krishna Mohan ELLURU ,  M Arun KUMAR ,  A Abdul SAMADH ,  Jayachandra Babu K

IPC: H04L12/26 ,  H04L29/06

Abstract: A system and a method for performing programmable analytics on network data are described. A data layer constructs flow behavior information based on information present within headers of data packets flowing across one or more network devices configured in a computer network. An inline heuristics layer performs one or more inline heuristic operations on the flow behavior information to obtain aggregate statistical information. An integrated analytics layer performs one or more analytical operations on the flow behavior information to obtain network insights. A presentation layer filters and plots information obtained from the data layer, the inline heuristics layer, and the integrated analytics layer, based on a user input.