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:
Nov. 23, 2021

Filed:

Oct. 12, 2018
Applicant:

International Business Machines Corporation, Armonk, NY (US);

Inventors:

Xiaokui Shu, Ossining, NY (US);

Zhongshu Gu, Ridgewood, NJ (US);

Heqing Huang, Mahweh, NJ (US);

Marc Philippe Stoecklin, White Plains, NY (US);

Jialong Zhang, White Plains, NY (US);

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
H04L 29/06 (2006.01); G06N 20/00 (2019.01); G06F 16/951 (2019.01);
U.S. Cl.
CPC ...
H04L 63/1425 (2013.01); G06F 16/951 (2019.01); G06N 20/00 (2019.01); H04L 63/1416 (2013.01); H04L 63/1433 (2013.01); H04L 63/20 (2013.01);
Abstract

An automated method for cyberattack detection and prevention in an endpoint. The technique monitors and protects the endpoint by recording inter-process events, creating an inter-process activity graph based on the recorded inter-process events, matching the inter-process activity (as represented in the activity graph) against known malicious or suspicious behavior (as embodied in a set of one or more pattern graphs), and performing a post-detection operation in response to a match between an inter-process activity and a known malicious or suspicious behavior pattern. Preferably, matching involves matching a subgraph in the activity graph with a known malicious or suspicious behavior pattern as represented in the pattern graph. During this processing, preferably both direct and indirect inter-process activities at the endpoint (or across a set of endpoints) are compared to the known behavior patterns. The approach herein provides for systematic modeling of inter-process behaviors for characterizing malicious or suspicious patterns among processes.


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