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Facia.ai
Company
About us Facia empowers businesses globally with with its cutting edge fastest liveness detection
Campus Ambassador Ensure countrywide security with centralised face recognition services
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Innovation Facia is at the forefront of groundbreaking advancements
Sustainability Facia’s Mission for a sustainable future.
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ABOUT US
Facia is the world's most accurate liveness & deepfake detection solution.
Facial Recognition
Face Recognition Face biometric analysis enabling face matching and face identification.
Photo ID Matching Match photos with ID documents to verify face similarity.
(1:N) Face Search Find a probe image in a large database of images to get matches.
DeepFake
Deepfake Detection New Find if you're dealing with a real or AI-generated image/video.
Detect E-Meeting Deepfakes Instantly detect deepfakes during online video conferencing meetings.
Liveness
Liveness Detection Prevent identity fraud with our fastest active and passive liveness detection.
Single Image Liveness New Detect if an image was captured from a live person or is fabricated.
More
Age Verification Estimate age fast and secure through facial features analysis.
Iris Recognition All-round hardware & software solutions for iris recognition applications.
Complete playbook to understand liveness detection industry.
Read to know all about liveness detection industry.
Industries
Retail Access loyalty benefits instantly with facial recognition, no physical cards.
Governments Ensure countrywide security with centralised face recognition services
Dating Apps Secure dating platforms by allowing real & authentic profiles only.
Event Management Secure premises and manage entry with innovative event management solutions.
Gambling Estimate age and confirm your customers are legitimate.
KYC Onboarding Prevent identity spoofing with a frictionless authentication process.
Banking & Financial Prevent financial fraud and onboard new customers with ease.
Contact Liveness Experts To evaluate your integration options.
Use Cases
Account De-Duplication (1:N) Find & eliminate duplicate accounts with our face search.
Access Control Implement identity & access management using face authorization.
Attendance System Implement an automated attendance process with face-based check-ins.
Surveillance Solutions Monitor & identify vulnerable entities via 1:N face search.
Immigration Automation Say goodbye to long queues with facial recognition immigration technology.
Detect E-Meeting Deepfakes New Instantly detect deepfakes during online video conferencing meetings.
Pay with Face Authorize payments using face instead of leak-able pins and passwords.
Facial Recognition Ticketing Enter designated venues simply using your face as the authorized ticket.
Passwordless Authentication Authenticate yourself securely without ever having to remember a password again.
Meeting Deepfake Detection
Know if the person you’re talking to is real or not.
Resources
Blogs Our thought dumps on all things happening in facial biometrics.
News Stay updated with the latest insights in the facial biometrics industry
Whitepapers Detailed reports on the latest problems in facial biometrics, and solutions.
Webinar Interesting discussions & debates on biometrics and digital identity.
Case Studies Read how we've enhanced security for businesses using face biometrics.
Press Release Most important updates about our activities, our people, and our solution.
Mobile SDK Getting started with our Software Development Kits
Developers Guide Learn how to integrate our APIs and SDKs in your software.
Knowledge Base Get to know the basic terms of facial biometrics industry.
Most important updates about our activities, our people, and our solution.
Buyers Guide
Complete playbook to understand liveness detection industry
In This Post
What’s the best way to stop an intruder before entering your premises? It is to identify an intruder outside the premises and report him right away to law enforcement. To do it in a frictionless manner, intrusion detection systems must be equipped with identity verification technology that is unconstrained, handy, speedy, and accurate. We prefer saying that biometrics like facial recognition is the best tool for intrusion prevention in multiple environments.
Let’s shed some light on using Face Recognition for Intrusion detection & prevention systems in today’s blog.
Generally, an Intrusion Detection System (IDS) is a security solution designed to detect unauthorized access and physical breaches within protected premises. Facial recognition technology is leveraged to enhance intrusion detection and prevention by recognizing and detecting the faces of intruders and differentiating them from allowed personnel in a monitored area.
Intrusion doesn’t only mean a physical unauthorized entry into a building or premises. Intrusion can also occur digitally where cybercriminals bypass the security barriers and break into restricted cyberspaces for many illicit gains:
Facial recognition tool in an intrusion prevention system will carry out a 1 to 1 and 1 to N face matching of a person whose face appears in front of an embedded device having a smart camera.
The comparison is carried out as:
If an identity doesn’t satisfy either of the above face-matching procedures, the system takes action against the individual by reporting the individual or alerting the security personnel to stop him.
Deep learning is a branch of Machine Learning that allows the use of neural networks (in this case Convolutional Neural Networks), composed of abundant layers that train a system by learning from represented input data at an increased level of abstraction in each layer. Security Intrusion Detection Systems have benefitted from Deep Learning models in the following ways:
Signature-based IDS works on known patterns of intrusion. It is a knowledge-based system that works with the matching methods and detects previous intrusion attempts. Simply, when an intrusion signature matches with a previously detected intrusion signature, the system raises the alarm.
Anomaly-based IDS (AIDS) is aimed at overcoming the loopholes in SIDS. It employs machine learning, knowledge-based, and statistical analysis methods. A significant deviation noted between the observed behavior and the model will be detected as an anomaly. This anomaly will be interpreted as an intrusion. It further involves 2 steps:
Just like other biometric authentication tools, intrusion detection systems using facial recognition are evaluated based on the following standard performance measures:
The threshold with which an IDS incorrectly authorizes an intruder or fails to detect an intrusion attempt.
It is the error rate with which an Intrusion Detection System falsely identifies a true user as an intruder.
It is the number of correct authentication of genuine users by an IDS using facial biometrics.
It is the number of correct detection intrusion attempts by an Intrusion Detection System.
It is the percentage of all correctly detected intruders and users to all the presented attempts. It measures the accuracy level of an intrusion detection system.
A report pinned the evolution of malicious software as the critical challenge intrusion detection systems (IDS) faced. Malicious attacks refer to the creation of highlight sophisticated and difficult-to-detect tactics to bypass intrusion detection in all settings. Pertinent to Facial recognition the creation of deepfake images and deepfake injection attacks have heightened the threat levels.
A deepfake is a highly convincing and realistic-looking picture, voice, or video manipulation technique that can confuse and outwit the biometric authentication used in intrusion prevention systems. Recently, deepfakes have been observed as one of the most threatening malicious attacks in the cyber world.
AI intrusion detection incorporates Liveness detection for enhanced intrusion detection and prevention. Facial recognition technology used for intrusion detection requires robust methods to detect anomalies and different malicious attacks such as deepfakes as discussed earlier. To detect and prevent these, an early liveness check will ensure that the person trying to enter cyberspace is a genuine permitted user and not a deepfake intrusion attack.
Facial recognition tools like Facia offer AI Liveness Detection to fortify the intrusion prevention system by detecting deepfakes and other spoofing attempts. It is a regularly updated liveness verification program that will give no breathing space to any intruder online and on-premises. Secure your buildings, online spaces, and beyond with Facia against intruders.
An intrusion detection system highly depends upon the robustness of the facial recognition solution deployed at the heart of identity verification to improve accuracy and speed of detection. Liveness plays a critical role in detecting cyber intrusion particularly the ones using deepfakes and other facial identity spoofing tactics. Opting for a robust liveness-based facial recognition tool will sow the seed of continuous improvement and prevent intrusion attempts in real-time.
Facial recognition plays a critical role in intrusion detection systems as it recognizes the faces of intruders and helps in accurately identifying authorized users and potentially threatening personnel.
Integrating facial recognition technology with an intrusion detection system enhances the overall security as accurately detecting faces is critical for the firm’s on-premises and online security. It does it by ensuring that no spoofing attack is carried out or no dangerous person has entered the space without going undetected. Once a face is recognized as an intruder the firm can take swift actions to stop the harmful activities.
Traditional methods of intrusion detection such as hiring security guards who personally keep a watch have loopholes like missing out on a random intruder or not having a clear view of the faces. They might even miss out on a possible mask attack or even they can easily be overpowered by an armed intruder if not properly equipped. Similarly, traditional intrusion detection in cybersecurity is also limited to carrying out simple security checks like security questions or a password. Facial recognition resolves both ends of the problem by offering liveness detection for accurately recognizing the faces of the individuals and reporting them.
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