In the past, people used passwords and PINs to protect their data. With the introduction of biometrics, like facial recognition, fingerprints, and iris scans, security improved by using physical traits for verification.
However, as technology advances, so do ways to bypass these systems. Biometric systems, once seen as more secure than passwords, are now vulnerable to attacks, such as hackers using high-quality photos or 3D models to trick facial recognition or creating fake fingerprints to fool scanners.
Finally, this raises an important question: is biometric authentication safe from manipulation? To learn more about this, let’s figure out the answer in the following paragraphs below.
What is Biometric Authentication?
Biometric authentication is a way to verify your identity using unique physical characteristics, like your fingerprint, face, voice, or even your eye’s iris. Instead of typing a password, the system checks these traits to confirm it’s really you. For example, when you unlock your phone with your face or fingerprint, that’s biometric authentication in action.
How Does Biometric Authentication Work?
How biometric authentication works is by using unique physical characteristics, such as fingerprints, facial features, or voice patterns, to verify your identity.
The process begins with enrollment, where your biometric data is captured and stored in the system. Instead of saving the actual image, the system stores a digital template that represents the unique patterns or features of your biometric data. This helps protect your privacy while enabling future verification.
When you attempt to authenticate, the system will capture a new scan of your biometric data, such as scanning your fingerprint or your face. This new data is compared to the stored template from the enrollment stage.
During the matching process, the system analyzes the captured data and looks for similarities or unique traits, like the ridge patterns in your fingerprint or key points on your face, to see if they match the stored template.
Finally, during verification, if the captured data closely matches the stored template, the system grants access. If there is a mismatch, access is denied.
Biometric Authentication Disadvantages
Biometric authentication advantages and disadvantages include the fact that while it provides a higher level of security compared to traditional methods like passwords, it is not immune to risks. Here are further explanations of some risks of biometric authentication:
1. Spoofing Attacks
Spoofing attacks are a type of cybercrime where hackers trick systems into thinking they are someone else in order to steal information or gain unauthorized access
In biometrics, this can involve using deep fakes like fake fingerprints, photos, or models to bypass security. These attacks can lead to data theft or financial loss, but using extra security steps and technology can help prevent them.
According to an article published by scworld.com, it’s mentioned that deepfake technology, combined with new malware like the GoldPickaxe trojan, poses a serious threat to biometric authentication.
Hackers can steal facial recognition data and use deepfakes to manipulate systems and access sensitive information, such as bank accounts. This highlights the growing risk of relying solely on biometrics for security and emphasizes the need for multi-factor authentication and better security measures to protect against such sophisticated attacks.
2. Data Breaches
Unlike a password, which can be reset, biometric features like fingerprints or facial recognition are permanent and cannot be changed.
If this data is breached, users are exposed to long-term risks. Stolen biometric data can be used to impersonate someone across various platforms, such as gaining access to devices or financial accounts.
Even though biometric systems may be encrypted, breaches still possibly occur, and the consequences of stolen biometric data are far more severe than losing a password.
3. Privacy Concerns
Privacy is a big concern with biometric authentication because our biometric data is unique and can’t be changed. This raises ethical issues about how it’s collected, stored, and used.
Many people worry that companies or governments may gather their data without consent. The rise of facial recognition, for example, has sparked debates about surveillance and losing anonymity. Some governments and corporations have been criticized for mishandling biometric data, putting personal privacy at serious risk if it’s compromised or shared without permission.
4. Limitations of Current Technology
Despite their growing popularity, current biometric authentication systems still have their flaws. For instance, fingerprint scanners may fail if your fingers are dirty, injured, or wet.
Similarly, facial recognition struggles in poor lighting or if you change your appearance, like growing a beard or wearing glasses. These limitations can make biometric systems less reliable and easier to fool.
AI Authentication: A More Robust Alternative
Biometric authentication, such as fingerprints or face recognition, has limitations like vulnerability to hacking, environmental factors, or being easily tricked by photos. These systems often fail in certain conditions, such as damaged fingerprints or altered appearances, making them less secure and reliable for long-term use.
Since hackers are using AI to bypass systems, we should enhance our identity verification methods by integrating AI as well.
AI authentication is a more robust alternative to biometrics because it goes beyond physical traits, like fingerprints or facial recognition, by analyzing behavioral patterns such as typing speed, mouse movements, and even walking style.
These traits are harder to replicate, making AI-based systems more secure against spoofing attempts.
So, how AI authentication works and what makes it better than biometric? Let’s figure out the answer below.
How AI Authentication Works
According to loginradius.com, AI-powered authentication uses machine learning to monitor and analyze how users behave, identify unusual activity, and verify identities instantly.
It can adjust to changing patterns and learn from the user’s actions over time. In other words AI continuously checks authentication and can spot suspicious behavior or unauthorized access attempts in real-time. Thus, they can notice if something is different and flag a suspicious activity.
To understand it better, here are a number of techniques used by AI authentication to verify your identity in smarter and more secure ways.
1. Behavioral Biometrics
This verification technique tracks how you interact with your device. For instance, the way you type, how you swipe on your phone, and how you hold it. Since each person has unique habits, AI can recognize your patterns and spot when something unusual happens. So, if someone else tries to use your phone, the AI may notice the difference in how they use it and flag the activity as suspicious.
2. Facial Recognition
We have already mentioned about the fraud that occurred using high quality photos or deep fakes. AI authentication allows us to prevent this by scanning your face through a camera and compares it to a stored image.
It can check for details like the distance between your eyes or the shape of your nose to confirm that it’s really you. This is commonly used in smartphones and security systems to unlock devices or access restricted areas.
3. Voice Recognition
AI can also recognize your voice, analyzing unique features like your tone, pitch, and speaking style. When you speak into a device, it compares your voice to a stored sample to make sure it’s you.
4. Fingerprint Recognition
Even though it’s not new, AI is making fingerprint scanning smarter. AI systems can analyze the unique patterns in your fingerprint more accurately and detect subtle differences, making the process quicker and more reliable.
5. Eye (Iris) Scanning
Iris scanning uses the unique patterns in the colored part of your eye to identify you. AI systems are able to capture detailed information about your iris and compare it with previously stored data. This method is very secure because the iris is difficult to replicate.
6. Continuous Authentication
Unlike traditional authentication that only checks your identity once, AI-powered systems can keep verifying you throughout your session.
For example, even after you’ve logged in with a password or fingerprint, AI can continue to monitor your behavior, such as how you use the device or your typing speed. If something feels off, like if someone else tries to access your account, the system can raise an alert or ask for additional verification.
AI systems learn and adapt based on the data they receive, continually refining their algorithms to enhance accuracy and security. By using behavioral biometrics, AI authentication creates a more robust security layer that goes beyond simple facial recognition or fingerprint scanning.
Main Benefits of AI Authentication
So, compared to biometrics, what makes AI authentication safer and more reliable?
1. Enhanced Security Against Manipulation
Unlike biometric systems that rely on static data like fingerprints or facial features, AI authentication tracks user behavior, making it harder for hackers to spoof. Even if hackers access a user’s biometric data, they would still need to replicate unique behavioral patterns to bypass security.
Additionally, AI can detect unusual behaviors in real time, such as logging in from a new location or typing inconsistently. If something seems off, the system can prompt for extra verification, adding an extra layer of security against unauthorized access and identity theft.
2. Improved Accuracy and Reliability
AI authentication systems are constantly improving their accuracy by learning from more data. Unlike biometric systems, which can be impacted by factors like poor lighting or physical injuries, AI focuses on patterns that are less affected by these variables. AI is also better at accommodating users with disabilities or unusual behaviors, ensuring smoother and more reliable authentication for everyone.
As AI systems analyze more data over time, they get better at identifying real users versus fraudsters, reducing the chances of false positives or negatives. This means the authentication process becomes more trustworthy and secure, lowering the risk of unauthorized access.
3. Enhanced User Experience
With AI, users enjoy enhanced security without needing to remember passwords or constantly scan their fingerprints. The system becomes more intuitive with each use, learning the user’s behavior and preferences, leading to a more effective and convenient authentication process.
Conclusion: So, Is Biometric Authentication Secure from Manipulation?
Biometric authentication is not fully safe from manipulation. Hackers can use methods like spoofing with fake fingerprints or face recognition images to bypass biometric systems.
In contrast, AI authentication offers a more robust alternative. It analyzes behavioral patterns, like typing speed or movement in real time, which are harder to replicate, and improves over time to detect fraud and enhance security.
Keypaz: AI-Powered Seamless Authentication
One example of AI-powered seamless authentication is Keypaz, a cutting-edge solution designed to provide robust security without compromising user experience. Keypaz uses AI to analyze a wide range of behavioral data to verify identity in real time.
With seamless AI authentication, it could secure your business from account takeover, payment fraud, promo abuse, and SMS fraud.
By continuously learning from user behavior, Keypaz adapts to new security challenges, offering a smooth, password-free experience while improving fraud detection. It ensures both security and convenience, making it a valuable tool for businesses looking to enhance digital security without compromising user experience.
To explore how we can assist you, feel free to reach out to us here.