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:
Mar. 24, 2020

Filed:

Jan. 24, 2019
Applicant:

Panasonic Intellectual Property Corporation of America, Torrance, CA (US);

Inventors:

Ryota Takahashi, Osaka, JP;

Takamitsu Sasaki, Osaka, JP;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
H04L 29/06 (2006.01); G06F 21/55 (2013.01); G06K 9/62 (2006.01); G07C 5/00 (2006.01); H04L 29/08 (2006.01); G06N 20/00 (2019.01); H04L 12/40 (2006.01); G06N 99/00 (2019.01); G07C 9/00 (2020.01);
U.S. Cl.
CPC ...
H04L 63/1425 (2013.01); G06F 21/55 (2013.01); G06F 21/552 (2013.01); G06F 21/554 (2013.01); G06K 9/6232 (2013.01); G06K 9/6262 (2013.01); G06K 9/6282 (2013.01); G06K 9/6284 (2013.01); G06K 9/6298 (2013.01); G06N 20/00 (2019.01); G06N 99/00 (2013.01); G07C 5/008 (2013.01); H04L 12/40 (2013.01); H04L 67/12 (2013.01); G07C 2009/00555 (2013.01); H04L 2012/40215 (2013.01);
Abstract

Provided is an information processing device that includes a processor and has a capability to detect abnormalities on an in-vehicle network that may be caused by an attack. The processor receives input of data elements to be used as training data, normalizes the training data so as to be distributed within a first region, divides a multi-dimensional second region that encompasses the first region into third regions that are hypercubes of equal sizes, obtains S data elements that are contained by each of the third regions, and for each third region that includes a number of data elements that is less than a first threshold value T, adds noise elements that are vectors with a uniform distribution to the third regions, generates noise-added training data including the vectors in the second region, and generates and outputs Isolation Forest learning model data by using the generated noise-added training data.


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