Living body detection method, system and non-transitory computer-readable recording medium

Patent metadata

Field	Value
Publication number	US-2020005019-A1
Application number	US-201816212410-A
Country	US
Kind code	A1
Filing date	Dec 6, 2018
Priority date	Jun 28, 2018
Publication date	Jan 2, 2020
Grant date	—

Abstract

There are provided in embodiments of the present disclosure a living body detection method, system and a non-transitory computer-readable recording medium. The living body detection method includes: acquiring device information of a terminal used to acquire an image of an object to be detected; determining a device risk level of the terminal; determining a living body detection strategy based on the device risk level of the terminal. The above technical solution adjusts the living body detection strategy by utilizing the device information of the terminal, which guarantee a true living body to go through a pass of the detection at a smaller cost, and at the same time makes it difficult for a false and malicious living body to go through a pass of the detection, thereby greatly reducing security risk of the living body detection, enhancing the user experience, and preventing the malicious request from occupying the system resources.

First claim

What is claimed is:

1 . A living body detection method, comprising:
acquiring device information of a terminal, wherein the terminal is used to acquire an image of an object to be detected; determining a device risk level of the terminal by utilizing the device information of the terminal; and determining a living body detection strategy based on the device risk level of the terminal.

2 . The method according to claim 1 , wherein the determining a device risk level of the terminal by utilizing the device information of the terminal comprises:
determining whether the terminal is a virtual machine according to the device information of the terminal, wherein a device risk level of the virtual machine is a high risk level.

3 . The method according to claim 2 , wherein the device information comprises one or more of:
a device fingerprint, information on device electric energy, or information on device sensor.

4 . The method according to claim 3 , wherein the device sensor comprises one or more of:
a gyroscope sensor, a gravity sensor, an acceleration sensor, or a magnetic sensor.

5 . The method according to claim 1 , wherein the device information comprises a device fingerprint, and the determining a device risk level of the terminal by utilizing the device information of the terminal comprises:
determining that the device risk level of the terminal is a high risk level if the device fingerprint of the terminal belongs to a device fingerprint high risk blacklist library; or determining that the device risk level of the terminal is a risk level if the device fingerprint of the terminal belongs to a device fingerprint risk blacklist library.

6 . The method according to claim 1 , wherein the device information comprises information on an abnormal accessing number of the terminal, and the determining a device risk level of the terminal by utilizing the device information of the terminal comprises:
determining that the device risk level of the terminal is a high risk level if the abnormal accessing number of the terminal is greater than a first threshold; or determining that the device risk level of the terminal is a risk level if the abnormal accessing number of the terminal is not greater than the first threshold but greater than a second threshold.

7 . The method according to claim 2 , wherein the determining a living body detection strategy based on the device risk level of the terminal comprises:
determining that the living body detection strategy is a refusal strategy if the device risk level of the terminal is a high risk level.

8 . The method according to claim 5 , wherein the determining a living body detection strategy based on the device risk level of the terminal comprises:
determining that the living body detecting strategy is to randomly increase a number of actions required to be performed by the object to be detected or raise difficulty of actions required to be performed by the object to be detected if the device risk level of the terminal is a risk level; or determining that the living body detecting strategy is to randomly decrease the number of actions required to be performed by the object to be detected or reduce difficulty of actions required to be performed by the object to be detected if the device risk level of the terminal is neither a high risk level nor a risk level.

9 . A system for living body detection, comprising:
a processer; and a storage; wherein a computer program instruction is stored in the storage, and the computer program instruction is used to perform a living body detection method when being ran by the processor, wherein the living body detection method comprises:
acquiring device information of a terminal, wherein the terminal is used to acquire an image of an object to be detected,
determining a device risk level of the terminal by utilizing the device information of the terminal, and
determining a living body detection strategy based on the device risk level of the terminal.

10 . The system for living body detection according to claim 9 , wherein the determining a device risk level of the terminal by utilizing the device information of the terminal when the computer program instruction being ran by the processor comprises:
determining whether the terminal is a virtual machine according to the device information of the terminal, wherein a device risk level of the virtual machine is a high risk level.

11 . The system for living body detection according to claim 10 , wherein the device information comprises one or more of:
a device fingerprint, information on device electric energy, or information on device sensor.

12 . The system for living body detection according to claim 11 , wherein the device sensor comprises one or more of: a gyroscope sensor, a gravity sensor, an acceleration sensor, or a magnetic sensor.

13 . The system for living body detection according to claim 9 , wherein the device information comprises a device fingerprint, and the determining a device risk level of the terminal by utilizing the device information of the terminal when the computer program instruction being ran by the processor comprises:
determining that the device risk level of the terminal is a high risk level if the device fingerprint of the terminal belongs to a device fingerprint high risk blacklist library, or determining that the device risk level of the terminal is a risk level if the device fingerprint of the terminal belongs to a device fingerprint risk blacklist library.

14 . The system for living body detection according to claim 9 , wherein the device information comprises information on an abnormal accessing number of the terminal, and the determining a device risk level of the terminal by utilizing the device information of the terminal when the computer program instruction being ran by the processor comprises:
determining that the device risk level of the terminal is a high risk level if the abnormal accessing number of the terminal is greater than a first threshold, or determining that the device risk level of the terminal is a risk level if the abnormal accessing number of the terminal is not greater than the first threshold but greater than a second threshold.

15 . The system for living body detection according to claim 10 , wherein the determining a living body detection strategy based on the device risk level of the terminal when the computer program instruction being ran by the processor comprises:
determining that the living body detection strategy is a refusal strategy if the device risk level of the terminal is a high risk level.

16 . The system for living body detection according to claim 13 , wherein the determining a living body detection strategy based on the device risk level of the terminal when the computer program instruction being ran by the processor comprises:
determining that the living body detecting strategy is to randomly increase a number of actions required to be performed by the object to be detected and/or raise difficulty of actions required to be performed by the object to be detected if the device risk level of the terminal is a risk level, or determining that the living body detecting strategy is to randomly decrease the number of actions required to be performed by the object to be detected or reduce difficulty of actions required to be performed by the object to be detected if the device risk level of the terminal is neither a high risk level nor a risk level.

17 . A non-transitory computer-readable recording medium on which a computer prog

Assignees

• Beijing Kuangshi Tech Co Ltd

Inventors

• Liu Haimin
• Long Junjie

Classifications

• G06F21/32 Primary

  using biometric data, e.g. fingerprints, iris scans or voiceprints · CPC title

• G06F2221/2113

  Multi-level security, e.g. mandatory access control · CPC title

• G06Q20/40145

  Biometric identity checks · CPC title

• G06Q20/4016

  involving fraud or risk level assessment in transaction processing · CPC title

• G06K9/00114 Primary

  Physics · mapped topic