IP Library › Granted Patent US 12,627,655
Granted Patent B2
US 12,627,655 · App. 17/687,211 · Granted May 12, 2026

Dynamic biometric combination authentication

Inventors: Douglas Max Grover (Rigby, ID); Michael F. Angelo (Houston, TX)
Assignee: Micro Focus LLC
H04L63/0861G06F21/32
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Quick Facts
Patent No.
US 12,627,655
App. No.
17/687,211
Granted
May 12, 2026
Kind
B2
Abstract

A request to authenticate a user is received. A random authentication pattern is generated. For example, the random authentication pattern may be for the user to provide a series of biometric scans and/or gesture scans. Instructions for the random authentication pattern are sent to a communication device (e.g., to a smartphone or smartwatch). A generated authentication pattern is received from the communication device. The generated authentication pattern is compared to a stored set of biometric scans and/or gestures scans that are based on the random authentication pattern. The user is authenticated based on the generated authentication pattern meeting a threshold by comparing the generated authentication pattern to the stored set of biometric scans and/or gestures scans.

Claims (46)

1 . A system comprising:

a microprocessor; and

a computer readable medium, coupled with the microprocessor and comprising microprocessor readable and executable instructions that, when executed by the microprocessor, cause the microprocessor to:

receive a request to authenticate a user;

generate a random authentication pattern, wherein the random authentication pattern comprises a dynamic combination of at least one biometric scan and at least one gesture scan;

send instructions for the random authentication pattern;

receive a generated authentication pattern;

compare the generated authentication pattern to a stored set of biometric scans that are based on the random authentication pattern;

authenticate the user based on the generated authentication pattern meeting a threshold using the stored set of biometric scans; and

detect an attack when at least one of the at least one biometric scan and the at least one gesture scan exhibits a lack of variation in data points relative to a previous biometric scan and/or a previous gesture scan for the user,

wherein the lack of variation is identified by a machine learning process as indicative of a playback attack.

2 . The system of claim 1 , wherein the random authentication pattern changed based on a number of authentications.

3 . The system of claim 1 , wherein instructions for the random authentication pattern are sent to a communication device via a network, wherein the received generated authentication pattern is received from the communication device via the network, and wherein the random authentication pattern is generated based, at least partially, on a type of the communication device associated with the request to authenticate the user.

4 . The system of claim 3 , wherein the communication device is a smartwatch and wherein the instructions for the random authentication pattern are for a series of biometric scans at different locations on a wrist of the user.

5 . The system of claim 1 , wherein the random authentication pattern includes direction information.

6 . The system of claim 3 , wherein the communication device comprises a fingerprint scanner and wherein the instructions for the random authentication pattern are for a series of biometric scans of one or more fingers and/or locations on the one or more fingers.

7 . The system of claim 3 , wherein the communication device comprises a camera and wherein the instructions for the random authentication pattern comprise a facial scan and one or more gesture scans.

8 . The system of claim 3 , wherein the generated authentication pattern is based on biometric types supported by the communication device.

9 . The system of claim 1 , wherein a length of the generated authentication pattern is different based on a type associated with the user.

10 . A method comprising:

receiving, by a microprocessor, a request to authenticate a user;

generating, by the microprocessor, a random authentication pattern, wherein the random authentication pattern comprises a dynamic combination of at least one biometric scan and at least one gesture scan;

sending, by the microprocessor, instructions for the random authentication pattern;

receiving, by the microprocessor, a generated authentication pattern;

comparing, by the microprocessor, the generated authentication pattern to a stored set of biometric scans that are based on the random authentication pattern; and

authenticating, by the microprocessor, the user based on the generated authentication pattern meeting a threshold using the stored set of biometric scans; and

detecting, by the microprocessor, an attack when at least one of the at least one biometric scan and the at least one gesture scan exhibits a lack of variation in data points relative to a previous biometric scan and/or a previous gesture scan for the user,

wherein the lack of variation is identified by a machine learning process as indicative of a playback attack.

11 . The method of claim 10 , wherein the random authentication pattern changes based on a number of authentications.

12 . The method of claim 10 , wherein the instructions for the random authentication pattern are sent to a communication device via a network, wherein the received generated authentication pattern is received from the communication device via the network, and wherein the random authentication pattern is generated based, at least partially, on a type of the communication device associated with the request to authenticate the user.

13 . The method of claim 12 , wherein the communication device is a smartwatch and wherein the instructions for the random authentication pattern are for a series of biometric scans at different locations on a wrist of the user.

14 . The method of claim 13 , wherein the random authentication pattern includes direction information.

15 . The method of claim 12 , wherein the communication device comprises a fingerprint scanner and wherein the instructions for the random authentication pattern are for a series of biometric scans of one or more fingers and/or locations on the one or more fingers.

16 . The method of claim 12 , wherein the communication device comprises a camera and wherein the instructions for the random authentication pattern comprise a facial scan and one or more gesture scans.

17 . The method of claim 12 , wherein the generated authentication pattern is based on biometric types supported by the communication device.

18 . The method of claim 10 , wherein a length of the generated authentication pattern is different based on a type associated with the user.

19 . A communication device comprising:

a microprocessor; and

a computer readable medium, coupled with the microprocessor and comprising microprocessor readable and executable instructions that, when executed by the microprocessor, cause the microprocessor to:

receive a request to authenticate a user;

generate a random authentication pattern, wherein the random authentication pattern comprises a dynamic combination of at least one biometric scan and at least one gesture scan;

receive, based on the random authentication pattern, a generated set of biometric scans from the user;

authenticate the user based on the generated set of biometric scans meeting a threshold using a stored set of biometric scans; and

detect an attack when at least one of the at least one biometric scan and the at least one gesture scan exhibits a lack of variation in data points relative to a previous biometric scan and/or a previous gesture scan for the user,

wherein the lack of variation is identified by a machine learning process as indicative of a playback attack.

20 . The communication device of claim 19 , wherein the communication device is a smartwatch.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Mar 4, 2022
From: GROVER, DOUGLAS MAX; ANGELO, MICHAEL F.
To: MICRO FOCUS LLC
Reel/Frame 059176/0425 →
Continuity (1)
Related Publication 20230283603A1 · Sep 7, 2023
References Cited (23)
US 10037528B2 · Gardiner · 2018 [cited by applicant]
US 10281953B2 · Von Badinski · 2019 [cited by applicant]
US 10528715B2 · Fukuda · 2020 [cited by applicant]
US 20040123115A1 · Schuba · 2004 [cited by examiner]
US 20050134427A1 · Hekimian · 2005 [cited by applicant]
US 20130104227A1 · Dow · 2013 [cited by examiner]
US 20140059673A1 · Azar · 2014 [cited by examiner]
US 20170011210A1 · Cheong · 2017 [cited by applicant]
US 20190188367A1 · Fukuda · 2019 [cited by examiner]
US 20190222576A1 · Borkar · 2019 [cited by examiner]
US 20200120081A1 · Sutrala · 2020 [cited by examiner]
US 20200384950A1 · Takeyasu · 2020 [cited by examiner]
US 20210075796A1 · Cuan · 2021 [cited by examiner]
CN 108697380A · 2018 [cited by applicant]
CN 208781239U · 2019 [cited by applicant]
EP 3073414B1 · 2019 [cited by applicant]
JP 2003058508A · 2003 [cited by examiner]
JP 2018018324A · 2018 [cited by examiner]
JP 2018128736A · 2018 [cited by examiner]
KR 101796352 · 2017 [cited by examiner]
KR 102194566B1 · 2020 [cited by applicant]
KR 20220026198 · 2022 [cited by examiner]
WO WO2020249889A1 · 2020 [cited by examiner]