With the advancement of technology, it’s never been easier for cybercriminals to access compromised credentials, deploy convincing social engineering attacks, or use deep fakes to defraud and exploit organizations. 

Thus, the quest for more effective and efficient fraud prevention methods is ongoing. Traditional security methods can come with trade-offs, like increased friction for users or limited adaptability to new threats. But, emerging technologies like behavioral biometrics offer a dynamic approach to fraud prevention, promising a more streamlined and frictionless experience for both organizations and users.

Behavioral biometrics evaluates a user’s activity patterns and device interactions to recognize trusted users and prevent fraud. This differs from physical biometric methods like using a person’s unique fingerprint, voice, or iris pattern to authenticate them. 

Each user develops unique behavioral habits and patterns when using certain devices–including how they move their mouse, hold their mobile phone, swipe a touch screen, or type on a keyboard. Thus, behavioral biometrics offers a way to monitor these activities and interactions to establish trust and defend against potential fraud. 

In other words, organizations can monitor user behaviors to assess whether they are the rightful account owner, if behaviors are inconsistent with typical patterns, or if they detect anomalous or non-human behavior, which could indicate fraud is underway.

Continuous Authentication

Behavioral biometrics is ideal in scenarios where continuous monitoring is crucial to uphold security. This might be during a financial transaction or when a user gains access to sensitive data. 

In these cases, behavioral biometrics systems will continue to assess the activities and device interactions of the user throughout a session to ensure they are the authorized user, even after bypassing initial authentication measures. 

Since evaluating behavioral biometrics is passive and occurs behind the scenes, it is non-intrusive and can be implemented continuously without impacting the user experience.

Fraud Prevention

Behavioral biometrics provides organizations with an additional layer of security to mitigate fraud. It helps distinguish between regular customers and fraudulent or bot-like behavior based on device movements or interactions. 

Namely, it can help prevent account takeover fraud by looking for signs of user behavior that are outside the norm of regular activity patterns. It can also help prevent new account fraud by examining the behavior of users as they register, identifying signs of non-human behavior to stop automated registrations by bots. In all of these cases, the system can flag suspicious activity for further investigation and help organizations become more proactive. 

This is particularly useful to enhance security in online banking, ecommerce, or any platform dealing with financial transactions. It provides an extra layer of defense against fraudulent activity, constantly monitoring for deviations from regular user behavior patterns.

Behavioral biometrics can be broken down into a few main categories, each providing a unique way to monitor and evaluate physical user activities. We’ll describe each in further detail below.

Keystroke Dynamics

Sometimes referred to as typing dynamics, measuring the rhythm, speed, and manner of how a person types is a common type of behavioral biometric. With keystroke dynamics, users can be profiled and identified based on how they type on a keyboard, the unique key combinations they use (whether they tend to use the left or right shift button more often), their error rate, and other factors.  

Specifically, this technology will measure metrics like the pressure placed on keys, dwell time (the amount of time that a key is pressed), and flight time (the duration between when a key is released and the next key is pressed). So, keystroke dynamics are not just focused on how fast a person types, but also on a user’s specific typing rhythm and style. 

In practice, a system can monitor the unique keystrokes of a user during a session and compare them to historical data to look for fraudulent or atypical behavior. If an account user is known for being a quick and accurate typer, the system may flag a session if it detects the current user is much slower and making more errors than what’s expected from the authorized user. 

Even when a user is new and not known, keystroke dynamics can be used to identify bots, whose typing patterns may be too even or too rapid when compared with human users.

Mouse Interactions

Similarly, behavioral biometric systems can track a user’s interaction with a computer mouse or touchpad, including the movements and clicks they make. This technology establishes a user’s unique pattern for using a mouse, which is used to create a unique profile that can help distinguish between them and a fraudster. 

In general, a system will track interactions like mouse location, length and pressure of button clicks, mouse movement speed, and more. Even small hand motions and gestures are detected and monitored with behavioral biometric technology. 

Each user has a unique pattern and style of using a mouse, helping systems determine when a device user is the authorized account holder, or when there’s suspicious activity. Let’s say a specific laptop user rarely uses the touchpad and instead uses an attached mouse with slow, fluid movements. During a session where the user is making erratic movements only on the touchpad and without using the mouse, they may be flagged. Again, the user needn’t be known to flag non-human mouse interactions, like mouse movements in unnaturally straight lines, for example.

Touchscreen Interactions 

A user’s touchscreen interactions can also be used to monitor for suspicious activity on a device. How a person scrolls up or down, the pressure they apply to the screen, and the speed of interactions are all important data points to help distinguish users from one another, and human users from bots. 

The system will assess the typical touchscreen interactions for a given user, creating a unique profile based on their behaviors. In the future, all touchscreen activities will be monitored and compared against this stored data to help ensure that only the rightful user has access to the device. 

For instance, if a device user normally scrolls on the left side of the screen (indicating they’re likely left-handed) and uses medium pressure, it would be abnormal if the user suddenly switched to scrolling on the left side of the touchscreen and using very light pressure.

Device Movement Patterns

How a person handles their device is another important behavioral biometric monitored to prevent fraud. This differs from how the user interacts with the touchscreen, instead focusing on the angle of how the device is held and the speed the device is moving. 

This relies on two sensors of a mobile device, the gyroscope, which measures the rotation and orientation of the device, as well as the accelerometer, which reflects the acceleration of the device's movement. 

Behavioral biometrics systems can analyze data from these sensors to create a profile of the user’s typical movements and behaviors. Detected anomalies may indicate potential fraud and trigger additional security measures like re-entering their password or another fingerprint or facial scan.

As we mentioned above, behavioral biometrics are distinctly different from traditional physical biometrics like a person’s facial geometry or fingerprint. As such, they play different roles when it comes to an organization’s identity verification and fraud prevention systems. 

While physical biometrics play a crucial role in the initial login process (comparing the user’s provided biometric data against a stored sample to verify their identity), behavioral biometrics contribute to continuous authentication. They help organizations identify anomalies during user sessions, offering enhanced security throughout the entire interaction.

Inherent vs. Acquired Physical Traits

Behavioral and physical biometrics are focused on two separate types of user traits. Traditional physical biometrics are concerned with a person's inherent physical traits that are unique to all other individuals. This includes features such as: 

• Fingerprints

• Iris/retina structure

• Facial features

• Vein pattern

• Voice pattern

On the other hand, behavioral biometrics focus on the patterns of behavior that a person has acquired over time. In other words, it’s concerned with what a user does as opposed to what they are.

Security Level

The level of security offered by each type of biometric authentication method and the associated risks also differ. 

If there is a security breach and users’ digitized physical biometric data becomes exposed, this could pose serious risks over the long term. Unlike a compromised password that can easily be updated by the user, their physical biometric traits are one-of-a-kind and cannot be changed if they come into the wrong hands. Physical biometrics are difficult to spoof, though it is still a risk posed by this technology. 

In contrast, behavioral biometrics offer a dynamic layer of security on top of other authentication methods. Rather than relying solely on a static set of physical biometric data, these systems build and adapt user profiles by collecting continuous, real-time behavioral data. Specific behavior patterns are highly difficult to replicate accurately, even if the data were compromised. Behavioral biometrics in combination with physical biometrics and other security measures make account compromise much less likely.

Continuous Authentication & User Experience

Another key difference between behavioral and physical biometrics is how they are used in authentication and identity-proofing systems. 

Traditional physical biometrics are used for one-time authentication. When a returning user wants to log into their account, they will provide the proper biometric information, like a facial scan, which is then compared against the stored data to determine if the person is the authorized account holder. 

In comparison, behavioral biometrics offers continuous analysis for ongoing user interactions in a system or application. Because behavioral biometrics technology is passive, it allows users to stay logged in without the need for explicit re-authentication actions.

Two common types of online fraud that threaten businesses today include account takeover fraud and new account fraud, both of which behavioral biometrics can help mitigate. 

With account takeover fraud, attackers will use compromised credentials, social engineering, session hijacking, or other methods to gain unauthorized access to an account and impersonate the real user for personal financial gain. 

Behavioral biometrics technology constantly monitors user behavior throughout a session to detect anomalies that may indicate the account has been compromised. So, organizations can be more proactive in detecting suspicious activity by terminating flagged sessions or requiring additional authentication. 

Similarly, behavioral biometric monitoring helps prevent new account fraud, which are cases where fraudsters create new online accounts using fake or compromised identity or information, or with the intention of committing fraud. Because many cases of new account fraud involve automating account creation, looking for signs of non-human behavior in keystroke dynamics, mouse movement, and touchscreen interactions will allow organizations to quickly identify and stop new account registration by bots.

Even though behavioral biometrics offers continuous monitoring and an extra layer of fraud defense, there are some limitations and privacy concerns associated with this technology. 

Review the following advantages and disadvantages of behavioral biometric technology to help determine if it’s the right fit for your organization.

Pros of Using Behavioral Biometrics

There are some significant advantages to using behavioral biometric technology: 

• Non-intrusive: It offers a frictionless experience that does not disrupt users’ sessions
  
  

• Continuous authentication: Analyzes behavioral data continuously and in real-time, helping organizations be more proactive with fraud detection
  
  

• Multimodal approach: Given the range of behavioral biometrics available for use, these systems can layer various types for enhanced security
  
  

• Adaptable: Adapts to changing behaviors over time, making it nearly impossible for fraudsters to accurately spoof or imitate the authorized user’s behavior patterns
  
  

• 0-day detection: Even new and unfamiliar malicious tools like BOTs, emulators, and RATs can be detected by their anomalous behavior that differs from typical user activity
  
  

• Low false positives: A high-quality behavioral biometric model leads to a lower false positive rate, though this can be impacted when dealing with more complex cases or a less accurate system

Cons of Using Behavioral Biometrics

Despite the impressive benefits of this technology, there are also some drawbacks that are worth mentioning:

• Accuracy challenges: These systems may not always be 100% accurate and create some false positives or negatives, influenced by environmental factors, natural behavior variability, and the complexity of certain behavior patterns
  
  

• Privacy concerns: Users may not be comfortable with their behaviors continuously monitored, stored, and analyzed for security purposes
  
  

• Device dependency: There is a potential for discrepancy if a user accesses their account from a new device, which may cause some friction even for authorized users
  
  

• Technical complexity: Implementing and managing these systems can be complex and requires a team to have specialized knowledge and skills for the best accuracy, especially when relying on models that are not pre-trained for specific security questions
  
  

• Resource intensive: These systems may require a large amount of computational power and storage, which can be limiting for certain organizations
  
  

• Regulatory compliance: This technology must comply with relevant data security and privacy regulations like GDPR, HIPAA, and others

Note that some of the challenges regarding technical complexity and resource intensiveness can be effectively mitigated by purchasing a purpose-built, cloud-based solution that takes the heavy lifting and storage off of your organization’s shoulders.

In a digital landscape rife with advanced technology, it’s become easier for fraudsters to replicate a person’s face, voice, or other features. Given this context, there is a demand for authentication methods that go beyond an individual’s physical traits. 

Though the efficacy and application of behavioral biometrics are still evolving, there is a rising curiosity about the meaningful potential that it offers. Especially when compared to static security methods, behavioral biometric technology stands out as a dynamic and adaptable approach that continuously monitors user behavior for signs of suspicious or fraudulent activity. Behavioral biometrics, used in conjunction with physical biometrics and other security measures, can greatly improve an organization’s security posture and help effectively fight fraud and decrease risk – while offering a smooth experience to trusted users.