公开(公告)号：US20250097263A1

公开(公告)日：2025-03-20

申请号：US18469117

申请日：2023-09-18

Applicant: Avast Software s.r.o.

Inventor： Sadia Afroz ,  Václav Belák ,  Kevin Roundy ,  Viliam Lisý ,  Petr Somol

IPC: H04L9/40 ,  H04L9/06 ,  H04L51/212 ,  H04L51/216

Abstract: Systems and methods enable a notification based on determining a particular electronic message is associated with a particular cluster of electronic messages. A plurality of electronic messages from a first plurality of accounts directed to a second plurality of accounts over a network are received. The plurality of electronic messages are compared to determine a plurality of clusters of electronic messages. A particular electronic message is received from a first particular account directed to a second particular account. The particular electronic message is compared to the plurality of clusters of electronic messages to determine that the particular electronic message is associated with a particular cluster of the plurality of clusters of electronic messages. A notification is provided based on the determining that the particular electronic message is associated with the particular cluster of the plurality of clusters of electronic messages.

公开(公告)号：US20220237289A1

公开(公告)日：2022-07-28

申请号：US17159909

申请日：2021-01-27

Applicant: Avast Software s.r.o.

Inventor： Tomas Pevny ,  Viliam Lisy ,  Branislav Bosansky ,  Michal Pechoucek ,  Vaclav Smidl ,  Petr Somol ,  Jakub Kroustek ,  Fabrizio Biondi

IPC: G06F21/56 ,  G06F21/53 ,  G06N3/08 ,  G06N3/04

Abstract: A malware classification is generated for an input data set with a human-readable explanation of the classification. An input data set having a hierarchical structure is received in a neural network that has an architecture based on a schema determined from a plurality of second input data sets and that is trained to classify received input data sets into one or more of a plurality of classes. An explanation is provided with the output of the neural network, the explanation comprising a subset of at least one input data set that caused the at least one input data set to be classified into a certain class using the schema of the generated neural network. The explanation may further be derived from the statistical contribution of one or more features of the input data set that caused the at least one input data set to be classified into a certain class.