


Facial recognition cases occur frequently. Can multi-modal biometric verification become a new 'silver bullet”?
According to the facial recognition security survey released by the Ministry of Public Security in recent years, existing facial recognition technology has serious security risks. Criminals use publicly available user photos to copy and attack through electronic screens. , 2D paper printing attacks, 3D mask attacks, deep forgery attacks, adversarial sample attacks, ROM hijacking attacks, link hijacking attacks and other forms have broken through the technical defense lines of hundreds of well-known APPs, causing serious technical risks.
Therefore, how to improve the capabilities of biometric verification and anti-counterfeiting and solve existing security risks has become the core issue of biometric verification and anti-counterfeiting in the financial industry. In order to overcome this difficulty, Zhongguancun Kejin has designed a multi-modal biological verification and anti-counterfeiting algorithm fusion system. Based on the technical solution of audio and video fusion, by integrating sound technology and organically combining it with existing visual technology, it can greatly improve biological verification. Verification and anti-counterfeiting capabilities not only solve existing security risks, but also break down usage restrictions. The application of this technology can meet user-level anti-counterfeiting needs and can also bring more possibilities to intelligent supervision in various fields.
The multi-modal biometric verification and anti-counterfeiting algorithm fusion system realizes dimensionality reduction to combat electronic screen replica attacks, 2D paper printing attacks, 3D mask attacks, deep forgery attacks and other face attacks Security issues, and can form differentiated scenario-driven verification solutions, provide enterprise-level security protection capabilities, and meet user-level verification and anti-counterfeiting needs.
In the [T·Talk] technology sharing event on August 25, we specially invited Mr. Feng Yue, director of Zhongguancun Kejin AI Security Attack and Defense Laboratory, to be a guest in the live broadcast room , revealing to the general audience the technical principles and practical details of the Zhongguancun Kejin multi-modal biological verification and anti-counterfeiting algorithm integration system. Whether you are a practitioner in the algorithm industry or a developer keen on bio-anti-counterfeiting technology, I believe you can gain some unique technical experience and technical practices from this sharing.
Welcome everyone to participate in August 25th, 20:00 pm
[T·Talk] technology sharing event
Scan the QR code on the poster and make an appointment for the live broadcast immediately
The above is the detailed content of Facial recognition cases occur frequently. Can multi-modal biometric verification become a new 'silver bullet”?. For more information, please follow other related articles on the PHP Chinese website!

Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

AI Hentai Generator
Generate AI Hentai for free.

Hot Article

Hot Tools

Notepad++7.3.1
Easy-to-use and free code editor

SublimeText3 Chinese version
Chinese version, very easy to use

Zend Studio 13.0.1
Powerful PHP integrated development environment

Dreamweaver CS6
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

Hot Topics

How do we implement the function of generating voice subtitles on this platform? When we are making some videos, in order to have more texture, or when narrating some stories, we need to add our subtitles, so that everyone can better understand the information of some of the videos above. It also plays a role in expression, but many users are not very familiar with automatic speech recognition and subtitle generation. No matter where it is, we can easily let you make better choices in various aspects. , if you also like it, you must not miss it. We need to slowly understand some functional skills, etc., hurry up and take a look with the editor, don't miss it.

How to do face recognition and face detection in C++? Introduction: Face recognition and face detection are important research directions in the field of computer vision. They are widely used in image processing, security monitoring and other fields. This article will introduce how to use C++ language for face recognition and face detection, and give corresponding code examples. 1. Face detection Face detection refers to the process of locating and identifying faces in a given image. OpenCV is a popular computer vision library that provides functions related to face detection. Below is a simple person

How to use WebSocket and JavaScript to implement an online speech recognition system Introduction: With the continuous development of technology, speech recognition technology has become an important part of the field of artificial intelligence. The online speech recognition system based on WebSocket and JavaScript has the characteristics of low latency, real-time and cross-platform, and has become a widely used solution. This article will introduce how to use WebSocket and JavaScript to implement an online speech recognition system.

1. Enter the control panel, find the [Speech Recognition] option, and turn it on. 2. When the speech recognition page pops up, select [Advanced Voice Options]. 3. Finally, uncheck [Run speech recognition at startup] in the User Settings column in the Voice Properties window.

Audio quality issues in voice speech recognition require specific code examples. In recent years, with the rapid development of artificial intelligence technology, voice speech recognition (Automatic Speech Recognition, referred to as ASR) has been widely used and researched. However, in practical applications, we often face audio quality problems, which directly affects the accuracy and performance of the ASR algorithm. This article will focus on audio quality issues in voice speech recognition and give specific code examples. audio quality for voice speech

Hello everyone, I am Kite. Two years ago, the need to convert audio and video files into text content was difficult to achieve, but now it can be easily solved in just a few minutes. It is said that in order to obtain training data, some companies have fully crawled videos on short video platforms such as Douyin and Kuaishou, and then extracted the audio from the videos and converted them into text form to be used as training corpus for big data models. If you need to convert a video or audio file to text, you can try this open source solution available today. For example, you can search for the specific time points when dialogues in film and television programs appear. Without further ado, let’s get to the point. Whisper is OpenAI’s open source Whisper. Of course it is written in Python. It only requires a few simple installation packages.

PHP study notes: Face recognition and image processing Preface: With the development of artificial intelligence technology, face recognition and image processing have become hot topics. In practical applications, face recognition and image processing are mostly used in security monitoring, face unlocking, card comparison, etc. As a commonly used server-side scripting language, PHP can also be used to implement functions related to face recognition and image processing. This article will take you through face recognition and image processing in PHP, with specific code examples. 1. Face recognition in PHP Face recognition is a

Speaker variation problem in voice gender recognition requires specific code examples. With the rapid development of speech technology, voice gender recognition has become an increasingly important field. It is widely used in many application scenarios, such as telephone customer service, voice assistants, etc. However, in voice gender recognition, we often encounter a challenge, that is, speaker variability. Speaker variation refers to differences in the phonetic characteristics of the voices of different individuals. Because individual voice characteristics are affected by many factors, such as gender, age, voice, etc.
