Living body detection method and device based on Turing test

Abstract

The embodiment of the invention provides a living body detection method and device based on a Turing test. According to one specific embodiment, the method comprises the steps of selecting a target Turing test question from a preset Turing test question set and sent to a client, wherein the target Turing test question is used for prompting an operation main body of the client to respond to a test question by executing limb actions; receiving execution result data fed back by the client for the target Turing test question, the execution result data including video data of the operation subject executing limb actions; based on the execution result data, determining whether the operation subject passes a target test result of a target Turing test question; wherein the target test result is used for determining a living body detection result for the operation subject.

Description

technical field [0001] The embodiment of this specification relates to the field of computer technology, and in particular to a method and device for live body detection based on the Turing test. Background technique [0002] With the rapid development of face recognition technology, face recognition technology is more and more used in people's daily life. For example, it is used in security, finance, e-commerce and other fields that require identity verification. The current face recognition technology has been greatly improved in terms of recognition accuracy, but the subsequent attacks have exposed the disadvantages of face recognition. For example, attackers may try to conduct malicious Attacks, as another example, attackers may carry out malicious attacks by simulating user operations on computers. If there are security issues in face recognition, it will lead to a series of account security issues, data security issues, privacy security issues, and so on. In order t...

AI Technical Summary

Problems solved by technology

The current face recognition technology has been greatly improved in terms of recognition accuracy, but the subsequent attacks have exposed the disadvantages of face recognition. For example, attackers may try to conduct malicious Attacks, as another example, attackers may carry out malicious attacks by simulating user operations on computers

If there are security issues in face recognition, it will lead to a series of account security issues, data security issues, privacy security issues, etc.

Images