公开(公告)号：US20200210871A1

公开(公告)日：2020-07-02

申请号：US16725906

申请日：2019-12-23

Applicant: Avast Software s.r.o.

Inventor： Galina Alperovich ,  Dmitry Kuznetsov ,  Rajarshi Gupta

IPC: G06N7/00 ,  G06N20/00 ,  G06N5/02

Abstract: Systems and methods for device type classification system include a rules engine and a machine learning engine. The machine learning engine can be trained using device type data from multiple networks. The machine learning engine and the rules engine can receive data for devices on a network at a first point in time. The data can be submitted to a rules engine and the machine learning engine, which each produce device type probabilities for devices on the network. The device type probabilities from the rules engine and the machine learning engine can be processed to determine device types for one or more devices on the network. As more data becomes available at later points in time, the additional data can be provided to the rules engine and the machine learning engine to update the device type determinations for the network.

公开(公告)号：US11586962B2

公开(公告)日：2023-02-21

申请号：US16725906

申请日：2019-12-23

Applicant: Avast Software s.r.o.

Inventor： Galina Alperovich ,  Dmitry Kuznetsov ,  Rajarshi Gupta

IPC: G06N7/00 ,  G06N5/02 ,  G06N20/00

Abstract: Systems and methods for device type classification system include a rules engine and a machine learning engine. The machine learning engine can be trained using device type data from multiple networks. The machine learning engine and the rules engine can receive data for devices on a network at a first point in time. The data can be submitted to a rules engine and the machine learning engine, which each produce device type probabilities for devices on the network. The device type probabilities from the rules engine and the machine learning engine can be processed to determine device types for one or more devices on the network. As more data becomes available at later points in time, the additional data can be provided to the rules engine and the machine learning engine to update the device type determinations for the network.

公开(公告)号：US20220342985A1

公开(公告)日：2022-10-27

申请号：US17238854

申请日：2021-04-23

Applicant: Avast Software s.r.o.

Inventor： Galina Alperovich ,  Otakar Jasek

IPC: G06F21/55 ,  G06F21/62

Abstract: Anomalous or unexpected system permissions in applications in a computing environment are identified by generating a statistical model at least in part from application permissions granted across a plurality of application types. One or more of the application permissions granted across a plurality of application types are identified as potentially unexpected dangerous permissions. The statistical model is used to determine whether a target application has at least one potentially dangerous permission that is not statistically likely for a target application type of the target application.