The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Jun. 21, 2022

Filed:

Dec. 17, 2019
Applicant:

AO Kaspersky Lab, Moscow, RU;

Inventors:

Alexey V. Monastyrsky, Moscow, RU;

Mikhail A. Pavlyushchik, Moscow, RU;

Alexey M. Romanenko, Moscow, RU;

Maxim Y. Golovkin, Moscow, RU;

Assignee:

AO KASPERSKY LAB, Moscow, RU;

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06F 21/55 (2013.01); G06F 21/52 (2013.01); G06F 21/56 (2013.01); H04W 12/128 (2021.01); G06F 21/54 (2013.01); H04L 9/40 (2022.01);
U.S. Cl.
CPC ...
G06F 21/554 (2013.01); G06F 21/52 (2013.01); G06F 21/54 (2013.01); G06F 21/56 (2013.01); G06F 21/561 (2013.01); G06F 21/563 (2013.01); H04L 63/1408 (2013.01); H04L 63/1441 (2013.01); H04W 12/128 (2021.01); G06F 2221/033 (2013.01); G06F 2221/034 (2013.01); H04L 63/145 (2013.01);
Abstract

A system and method is provided for detecting anomalous events based on a dump of an address space of a software process in a memory of a computing device. An exemplary method includes detecting at least one event occurring in an operating system of the computing device during an execution of the software process, determining a context of the detected event, wherein the context comprises a dump of an address space of the software process containing code that was being executed at the moment of occurrence of the detected event, selecting a set of features of the dump for use in determining whether or not the event is anomalous, transforming the selected set of features of the dump into a convolution, determining a popularity of the convolution by polling a database, and determining that the detected event is an anomalous event if the determined popularity is below a threshold value.


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