Liveness Detection – Preventing Businesses From Biometric Spoofs

Imagine receiving a video call from a company you admire, offering a cash prize of $5 million. Exciting, right? But what if this call was a carefully crafted deepfake designed to steal your personal and financial information? This is where face liveness detection identifies and prevents such scams. Many organizations such as banks, fintech companies, and corporate security firms are using this method to verify their clients and users to avoid such scams. 

Facial liveness detection is a technique in which the system verifies that the person in front of the camera is genuine and not a fake representation such as a picture, digital image, or mask. If integrated with a biometric system then it can be incorporated with facial recognition, iris, and fingerprint scanning. Fraudsters frequently employ silicon masks, paper images, and forged identities to gain access to any account. Furthermore, when it comes to iris scanning, fraudsters frequently imitate the eyeballs to bypass biometric authentication. Cornell University researchers reported 98% accuracy in continuous liveness identification with a 2% EER (Equal Error Rate) in text-independent instances. It means that the system doesn’t work on pre-defined inputs but focuses on evaluating natural behaviors. 

How Does the Technology Work?

The technology has changed over time, with each advancement bringing additional functionality. Liveness detection methods are introduced in reaction to the spoofing attacks. It will work efficiently when implemented with biometric systems for ensuring safety. Businesses face issues like data breaches, presentation attacks, and other fraudulent activities. They continue to introduce new ways of spoofing, while tech companies introduce new methods and deepfake detection tools to aid in the prevention of fraud in businesses and other organizations. Essentially, there are two methods of detection: 

• Active Liveness Detection
• Passive Liveness Detection

Active liveness necessitates direct user engagement and demands for specific behaviors such as inserting a fingerprint, blinking, smiling, moving the head, and more. For example, challenge and response evaluation fall under this detection method. This evaluation also requires the user to perform the requested action, after which the system validates the person’s identity.

Passive liveness does not involve direct user interaction, but instead occurs throughout typical investigation. The technology captures the user’s natural movements for verification. Such verification is more user-friendly and time-saving. As per the study, 99.9% of users successfully completed passive liveness detection. The prior requires more effort due to the direct interaction and increased time consumption.  

Approaches of Liveness Detection

Liveness detection for face recognition employs a variety of techniques that can determine whether the provided biometric data is from a living human being. Here are some of the ways that can be utilized to improve liveness detection: 

Motion Analysis

Organizations utilize motion analysis to ensure the legitimacy of their customers. This technique exploits the individual’s natural dynamic movements, such as blinking. Blinking can also contribute to the detection of spoofs. Every human blinks approximately 30 times each minute, with each blink lasting 250 milliseconds on average. So, it can be captured by a generic camera for detection and can be an effective way to look for the liveness of a person. Other movements include tilting the head, smiling, chatting, moving the eyes, and naturally contracting the muscles.  

Texture Examination

This approach concentrates on the finer aspects of the skin. It recognizes fine lines, wrinkles, and pores. Natural skin also emits heat, which cannot be compared with the natural body heat emission. Such natural indicators can be useful for detecting liveness. The technology uses infrared sensors to read the skin’s texture in depth. 

Life Sign Analysis

Depending on the liveness indicators, organizations use a mixed strategy to verify customers. It requires detecting indicators of life in an individual by examining its texture, natural movements, body heat, heartbeat monitoring, and so on. Some of the real-world applications include securing transactions, verifying identities at airports, and more. This multimodal technique improves identification by combining several liveness markers in the process. 

Benefits of Liveness Detection

According to a DATAINTELO study, the global liveness detection market is predicted to be worth $ 1.5 billion in 2023, rising to $ 6.8 billion by 2032, due to the increasing thefts. Many businesses like banks, healthcare, and airports are using biometric liveness detection devices to avoid fraud on their premises. Here’s why firms are implementing this technology: 

Enhanced Security

Liveness detection, when integrated into biometric systems, can easily recognize digitally generated faces, printed photographs, silicon masks, and other objects. It guarantees security and prevents potential scams within the firm. 

Trust Building

Face liveness detection has acquired the trust of users in many businesses because it creates a sense of security by preventing sensitive information from being accessed.  For instance, in banking, it can deny the access to the illegitimate users. Similarly, in healthcare sectors, it can be used to prevent data breaches and protect sensitive information of patients. 

Real-Time Detection

The liveness detection technology provides effective real-time monitoring. It requires keeping an eye on people at grand events and recognizing potential risks, such as identifying identities and high-level risk individuals in crowded areas.  

Improved User Experience

Liveness detection technology integrated with biometric systems offers quite a handy experience to the users. Biometric solutions, such as iris and facial scans, provide an additional layer of security while making the process more user-friendly and efficient.  

Less Human Intervention

The automated liveness detection technology eliminates the need for manual checks, which have a higher risk of errors. The method becomes less time-consuming and cost-effective, resulting in improved verification. 

Situations Where Faces Are Undetectable 

The liveness detection system employs computer vision to distinguish between the user’s real and static images. Fraudsters may utilize silicon masks, printed pictures, or other spoofs to mislead the system. There is a strong need to implement liveness detection software in the organization to prevent fraud timely. According to the analysis, worldwide online fraud losses are predicted to rise by $362 billion between 2023 and 2028. Here are some of the situations that make faces undetectable: 

• Without a liveness verification system, businesses may have problems with AI-generated images, printed or digital photos, rather than real people. Image recognition is also important to prevent spoofing. Using liveness detectors can aid in detecting natural movements and identifying indicators of life. These technologies also use fingerprint and iris scans to determine whether a person is alive. 
• When it comes to videos, AI-generated content is immediately distinguishable from real content. The liveness detection algorithm can detect subtle inconsistencies like robotic movements, blurred edges, and much more.
• Masks are used to conceal the true identity. Fraudsters use silicon masks and other realistic disguises to impersonate someone using their identity. 

It is beneficial for businesses to understand such undetectable features. Integrating liveness detection technologies with biometric systems can improve security measures and deter criminal activity.  

Conclusion

Biometric verification systems when complemented with the liveness check, empower the system to deal efficiently with fraudulent activities. As the threats evolve, liveness detection technology will become more sophisticated in ensuring the security, and trust of the users, and preventing scams. This technology will always remain a vital tool for businesses to maintain integrity and reliability in the marketplace.