Biometric authentication refers to a cybersecurity process that verifies a user's identity using their unique biological characteristics, such as fingerprints, voice, retina, and facial features. Biometric authentication systems store this information to verify the user's identity when they access their account. This type of authentication is generally more secure than traditional forms of multi-factor authentication. In this system, facial and voice recognition are used for individual authentication.
Facial recognition is a biometric technology that identifies and verifies individuals by analyzing patterns obtained from a person's face. In recent years, facial recognition technology has been used in various fields, from unlocking smartphone screens to critical security applications in different organizations. The ability to be used for various purposes has made facial recognition technology widely applicable and popular among different organizations and companies.
Facial recognition technology has numerous advantages over older biometric techniques. It does not require direct contact with the individual, can be used from a distance, and does not need human intervention for identification. Additionally, it can track individuals based on time and their presence in specific locations. Since facial recognition technology involves fewer processes compared to older biometric methods, it is relatively cost-effective.
The facial recognition system consists of four subsections:
Face Detection
- In this subsection, the location of the face in the image is identified.
Face Alignment
- In this subsection, if the face is angled, it is converted to a standard form. If the face is significantly different from a frontal view, the system will reject the image.
Face Modeling
- Face modeling involves extracting resilient and unique features from the face for matching.
Face Matching
- In this subsection, the system compares the face model in the registered image (e.g., national ID card) with the person's face.
Additionally, in speaker authentication, the goal is to determine whether the claimed individual matches their voice sample.
This system uses deep learning methods to detect and recognize faces in images captured from cameras.
Features of the Biometric Authentication System:
- Simultaneous processing of multiple faces
- Requires only one sample of the face for training
- Uses multiple samples of a face to increase accuracy
- Resistant to environmental changes like lighting and facial angles
- Real-time face detection with low-quality input
- Live face detection
Features of the Speaker Authentication System:
- Speaker identification
- Speaker diarization
- 95% accuracy in timely identification
- Resistant to environmental noise
Which organizations and companies can use biometric authentication?
Mobile Banking
Biometric security is one of the main challenges for banks and fintech companies. They use biometrics to authenticate transactions performed through mobile banking. Additionally, banks use biometric authentication to verify customers' identities when they attempt to access their mobile banking apps or accounts. Some financial institutions also consider biometric authentication as a replacement for PINs or passwords and even digital signatures.
Online Retail
Another popular application—especially for facial recognition—is in online retail or e-commerce. Online shoppers often abandon their carts or purchases if they forget their passwords or find the usual login method too time-consuming. Facial biometric authentication can solve this problem for online shoppers and improve retail business.
Healthcare
Biometric authentication also has widespread applications in the healthcare sector. Biometric information—obtained through fingerprint and iris scans and facial recognition—enables hospitals to identify patients and retrieve their medical history. This ensures that healthcare centers can provide appropriate treatment with access to accurate information.