Face Liveness Pro

Spoofs or Presentation Attacks involve representations of human faces used by fraudsters to deceive face biometric systems and commit identity theft. Our Facial Liveness Pro API can distinguish a live person from a spoofing attack through Liveness Detection or Presentation Attack Detection (PAD) along with Deepfakes detection. Unlike most other systems that perform PAD, our Facial Liveness does not require any action or movement — it only requires a single image of the user taken from the front camera of their phone.

Types of Presentation Attacks

Advanced Fraud Detection

The Face Liveness Pro API detects not only spoofing attempts but also advanced fraudulent techniques:

• Deepfakes — Hyper-realistic images created using deep learning algorithms to replace one person's face with another's. The API detects subtle inconsistencies and artifacts unique to deepfakes, ensuring genuine images pass verification.

• Generative AI Avatars — Highly realistic synthetic faces created using AI techniques like GANs. The API identifies these synthetic images by analyzing patterns and data structures that differ from real human faces.

The API returns a score and percentage used to determine liveness and deepfake detection.

Image Guidelines

curl -X POST "https://api.syntizen.com/CheckLivenessPro" \  -H "apikey: 0" \  -H "authkey: string" \  -H "Content-Type: application/json" \  -d '{    "rrn": "23242456234",    "type": "LIVENESS",    "isvkyc": "0",    "liveimage": "base64 image"  }'

{
  "respcode": "200",
  "respdesc": "success",
  "rrn": "23242456234",
  "liveness_results": {
    "liveness_description": "real",
    "liveness_score": 0.9767711162567139,
    "liveness_percentage": "97.68"
  }
}

{
  "respcode": "400",
  "respdesc": "Bad Request - Missing or invalid request parameters"
}

{
  "respcode": "401",
  "respdesc": "Unauthorized - Invalid or expired auth key"
}