Liveness Detection Technology

Trust in Liveness:
only real people allowed

Incode’s Liveness Detection technology ensures that only real, live people are verified. Achieve zero false positives (false approvals) and zero false negatives (false rejections) powered by advanced machine learning.

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Risks for your business

Evolving fraud puts your business and customers at greater risk

Generative AI is driving more sophisticated and frequent identity fraud, making it harder than ever to differentiate between legitimate users and fraudsters. The financial and reputational damage this can cause puts your business at serious risk.

Identity fraud losses in the United States alone could reach to US$40 billion annually by 2027.

Source: Deloitte

The person behind the camera could be a fraudster.
Not a live, genuine individual.

Is your business ready to face today’s
fraud threats?

With the complexity of fraud increasing at an accelerating rate, most identity verification providers
are unequipped to address this dramatic increase in identity fraud and deepfake attacks.

30x

increase in deepfakes from
2022 to 2023*

70%

of businesses claim identity fraud losses have increased in recent years*

*Source: 2023 Experian’s Identity and Fraud Report. Learn more

How AI is exploited for identity fraud

Fraudsters use a range of techniques to bypass
liveness detection systems

Deepfake and digital attacks

AI-generated deepfakes and advanced digital manipulation techniques.

Physical presentation attacks

Counterfeit visual data aimed at deceiving camera-based verification systems.

Evasion attacks

Face modifications aimed at deceiving recognition systems.

Seamless user experience

What happens behind the curtain
of invisible liveness detection

No friction, no user interaction needed. Our multi-frame liveness detection
verifies real people from manipulated and synthetic images and video.

What the user
experiences

What happens in the background

In real time, the system verifies the user’s biometrics to ensure the person is real.

● Physical Spoof Check
● Evasion Check
● Digital Spoof Check

How our technology works

The advanced technology
behind Liveness Detection

Our liveness detection technology combines digital, physical, and evasion spoof detection,
doubling the effectiveness and detection rate over using these methods independently.

Other models today

These error-prone models rely on a single input—typically a 2D image—and analyze multiple frames to enhance accuracy. However, they struggle to detect complex spoofing attempts, resulting in a less engaging user experience and diminished effectiveness in security and identification accuracy.

Incode Liveness (0,0) model

Our model enhances facial capture accuracy by selecting optimal frames and incorporating multiple modalities such as video, depth, and motion sensors. This approach closely mimics real-life interactions, significantly reducing both false negatives and false positives, and improving verification reliability.

The foundation of our proprietary technology

In-house Fraud Lab: real-time
adaptation to emerging threats

Stay ahead of evolving threats with our proprietary technology

Our Liveness Detection is powered by Incode’s Fraud Lab, where our team continuously refines our proprietary technology in response to emerging fraud techniques. Unlike competitors who rely on third parties, we can immediately address new fraud vectors, offering real-
time protection for your business.

Gain the competitive edge with instant fraud detection and response

Whenever a new attack vector arises, our Fraud Lab has the capacity to react instantly reacts instantly —detecting, analyzing, and neutralizing threats before they impact your operations. This agility ensures your business stays ahead in the ever-evolving fraud landscape.

Certified excellence in liveness detection

Industry-leading liveness detection and identity verification standards

iBeta level 1

Incode achieved the first iBeta Level 1 certification for passive liveness.

iBeta level 2

Incode achieved iBeta Level 2 certification, boosting model performance up to 50x.

ISO 30107-3

We adhere to standards for Presentation Attack Detection (PAD).

Gartner Leader in Completeness of Vision

Incode was named Leader in Gartner’s first Magic Quadrant for Identity Verification in 2024.

NIST Face Recognition Accuracy

Incode’s leading technology ranked among the top 10 global vendors.

Third-party verified Liveness
technology for real-world readiness

2024 the Georgia Department of Driver’s Services (GA DDS) test

0 False Positive Rate (FPR) and 0 False Negative Rate (FNR)

2024 the Georgia Department of Driver’s Services (GA DDS) test

0 False Positive Rate (FPR) and 0 False Negative Rate (FNR)

In 2024 the Georgia Department of Driver’s Services (GA DDS) performed an independent testing of Incode’s Liveness according to iBeta level 2 protocols, and we achieved 0 APCER (false positive rate / false acceptance of fraudulent users) and 0 BPCER (false negative rate / false rejections of genuine users).

Michigan State University’s Mobile Face Spoofing Database (MSU-MFSD) independently evaluated Incode

0% false positives and 0% false negatives confirmed

Incode’s tech conquers fraud prevention challenge from Michigan State University

0% false positives and 0% false negatives confirmed

In 2023, Michigan State University’s Mobile Face Spoofing Database (MSU-MFSD) evaluated Incode’s Liveness technology using a public dataset designed to test systems against face spoofing attacks. The evaluation confirmed our system’s precision, achieving 0% FPR (False Positive Rate) and 0% FNR (False Negative Rate).