公开(公告)号：US20190012351A1

公开(公告)日：2019-01-10

申请号：US15750587

申请日：2015-08-10

Applicant: Hewlett Packard Enterprise Development LP

Inventor： Alina Maor ,  Renato Keshet ,  Ron Maurer ,  Yaniv Sabo

IPC: G06F17/30 ,  G06F17/18

CPC classification number: G06F16/2462 ,  G06F16/24578 ,  G06F16/285 ,  G06F16/288 ,  G06F17/18 ,  G06F21/00 ,  G06F21/552 ,  G06N7/005 ,  G06N20/00

Abstract: The present disclosure provides a method, system and non-transient computer readable medium for evaluating system behaviour by deriving a statistical distance between each entity in a multi-entity system, and summing the statistical distance to each other entity to create a ranked abnormality score for each entity in the system.

公开(公告)号：US10255084B2

公开(公告)日：2019-04-09

申请号：US15184478

申请日：2016-06-16

Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP

Inventor： Olga Shain ,  Yaniv Sabo ,  Renato Keshet

IPC: G06F3/0481 ,  G06F9/451 ,  G06F17/30

Abstract: The present disclosure relates to an interactive system that manages analytics contexts through a series of analytics interactions. The disclosed interactive system receives a selection of an analytics interaction from a user during an interactive analytics session. Then, the system generates a series of analytics interactions by the user during the interactive analytics session. Each analytics interaction represents an analytics context that comprises an analytics interaction, a result, and a reference analytics context. Moreover, the system manages a plurality of analytics contexts by selecting the reference analytics context from previous analytics interactions, or by navigating to a different analytics context, or by deactivating a user-selected analytics context, and presents to the user the series of analytics interactions with the result corresponding to both the selection of the analytics interaction and the reference analytics context. Each analytics interaction in the series of analytics interactions is selectable by the user.

公开(公告)号：US20170149810A1

公开(公告)日：2017-05-25

申请号：US14951807

申请日：2015-11-25

Applicant: Hewlett Packard Enterprise Development LP

Inventor： Renato Keshet ,  Justin Scaggs ,  Yaniv Sabo ,  Ron Maurer ,  Hila Nachlieli ,  Alina Maor ,  Olga Shain ,  Alexander Maydanik

IPC: H04L29/06

CPC classification number: H04L63/1425 ,  H04L63/0281 ,  H04L63/145

Abstract: An interactive system to detect malware is provided to interactively analyze web proxy log data. The log data is progressively processed to compute analytics for different context settings. The system has a context module, an interaction module and a plurality of analytics modules. When a change of the context setting (filter, weights etc.) is requested, the processing and calculation of analytics for the current context setting is paused and subsequently restarted for the now changed context setting. An analytics interface provided via a graphical user interface is updated upon the change of context settings.

公开(公告)号：US10803074B2

公开(公告)日：2020-10-13

申请号：US15750587

申请日：2015-08-10

Applicant: Hewlett Packard Enterprise Development LP

Inventor： Alina Maor ,  Renato Keshet ,  Ron Maurer ,  Yaniv Sabo

IPC: G06F16/00 ,  G06F16/2458 ,  G06F16/28 ,  G06F21/00 ,  G06F21/55 ,  G06N7/00 ,  G06N20/00 ,  G06F16/2457 ,  G06F17/18

Abstract: The present disclosure provides a method, system and non-transient computer readable medium for evaluating system behaviour by deriving a statistical distance between each entity in a multi-entity system, and summing the statistical distance to each other entity to create a ranked abnormality score for each entity in the system.

公开(公告)号：US20180248900A1

公开(公告)日：2018-08-30

申请号：US15445477

申请日：2017-02-28

Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP

Inventor： Renato Keshet ,  Yaniv Sabo

IPC: H04L29/06 ,  G06F21/55

CPC classification number: H04L63/1425 ,  G06F21/552 ,  G06N20/10

Abstract: In some examples, a plurality of multi-dimensional data samples representing respective behaviors of entities in a computing environment are sorted, where the sorting is based on values of dimensions of each respective multi-dimensional data sample. For a given multi-dimensional data sample, a subset of the plurality of multi-dimensional data samples is selected based on the sorting. An anomaly indication is computed for the given multi-dimensional data sample based on applying a function on the multi-dimensional data samples in the subset. It is determined whether the given multi-dimensional data sample represents an anomalous entity in the computing environment based on the computed anomaly indication.

公开(公告)号：US20170364373A1

公开(公告)日：2017-12-21

申请号：US15184478

申请日：2016-06-16

Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP

Inventor： Olga Shain ,  Yaniv Sabo ,  Renato Keshet

IPC: G06F9/44 ,  G06F17/30 ,  G06F3/0481

CPC classification number: G06F9/453 ,  G06F3/04817 ,  G06F17/3053

Abstract: The present disclosure relates to an interactive system that manages analytics contexts through a series of analytics interactions. The disclosed interactive system receives a selection of an analytics interaction from a user during an interactive analytics session. Then, the system generates a series of analytics interactions by the user during the interactive analytics session. Each analytics interaction represents an analytics context that comprises an analytics interaction, a result, and a reference analytics context. Moreover, the system manages a plurality of analytics contexts by selecting the reference analytics context from previous analytics interactions, or by navigating to a different analytics context, or by deactivating a user-selected analytics context, and presents to the user the series of analytics interactions with the result corresponding to both the selection of the analytics interaction and the reference analytics context. Each analytics interaction in the series of analytics interactions is selectable by the user.