Meta: Biometric authentication systems employ a liveness detection feature to fight against the fraudulent attempts of online scammers and ensure online platform security.
The digital world is prone to several cyberattacks among which identity theft is considered the one increasing at a high rate. The exponential increase in the last year was recorded by the Federal Trade Commission when it received about 3.2 million reports related to consumer digital protection issues. The cyberattacks incidents take place at a big scale which varies from data breaches to account takeover fraud and financial crimes. These cyber-attacks compromise the financial and personal information of millions of customers of reputed brands which end up with high regulatory penalties from the regulators.
The massive increase in incidences of data breaches contributes highly to a 120% increase in cyber frauds such as identity theft and account take over. A major reason behind data breach is unauthorized access over user online accounts. The traditional identity authentication methods in the form of passwords and PINs are not strong enough to fight against the fraudulent tricks of bad actors. The online platforms have recognized the need for stringent authentication measures among which biometric authentication is leading.
Biometric authentication processes use unique biological traits of humans to identify and differentiate them from other individuals. The biometrics such as fingerprints, hand geometry, iris or retina, face, and voice acoustics are used for identity authentication. The online platforms employing the old traditional methods of user authentication are more prone to cyberattacks. The reason is that fraudsters have come up with the tricks to successfully forge the system. For example credential stuffing techniques are used in which the hackers run the malicious executable program that checks for all the possible credential combinations to get access over user accounts.
Advanced Online Biometric Authentication
Biometric authentication is also prone to fraudulent attempts but technological advancement has employed advanced algorithms of Machine learning and Artificial Intelligence to fight against those attempts. The facial recognition biometric systems are tempered using deep fakes, makeup attacks and 3D masks spoofing attacks. Some use printed pictures of faces to get access to online accounts of real users.
Identifying the scope of innovation, biometric authentication systems are revamped accordingly now that they have embedded fraud detection capability that identifies and verifies the spoofing elements from the picture to deter the risk of fraud. Advanced biometric services are adopted by the digital banking industry, e-commerce, and healthcare industry the most to ensure controlled and secure access over online user accounts.
Liveness Detection – Fights against Spoofing Attacks
Attackers use spoofing techniques and imitate the physical presence of a real user for authentication. The facial biometric authentication systems identify the face biometrics and match them against the ones previously stored in the database. If both match, identity is verified. However, simple biometric authentication methods are prone to deep fakes. To cater to these, advanced biometric authentication services use innovative AI-powered algorithms to fight against fraudulent attempts.
Liveness detection in the facial biometrics authentication systems helps ensure the physical presence of individuals at the time of identity authentication. The AI-powered system identifies the minor facial movements of individuals and asks to perform some actions to make sure that at the time of authentication, it is the real user present before the system.
The minor facial actions include the blinking of an eye, lip movement, and body movements. Liveness detection feature of biometric authentication identifies the spoofing tricks of fraudsters and rejects authentication. Hence ensures the security of the platform as well as the seamless online user experience.