Beyond Fingerprints: Exploring Behavioral Biometrics for Secure Identity Verification

Behavioral biometrics is a cornerstone of Zero Trust architecture. In our previous article, Cloud Security and Zero Trust, we outlined how the NIST (National Institute of Standards and Technology) defines Zero Trust as a cybersecurity paradigm focused on resource protection and the premise that trust is never granted implicitly but must be continually evaluated. They go on to say, the goal [is] to prevent unauthorized access to data and services coupled with making the access control enforcement as granular as possible. Behavioral biometrics is a form of advanced authentication that uses unique behavioral patterns to verify a user's identity. Unlike traditional biometrics, which rely on physical characteristics such as fingerprints or facial recognition, behavioral biometrics measures how a user interacts with a system, including their keystrokes, mouse movements, and other behavioral patterns unique to the individual.

By analyzing user-specific behavioral patterns, behavioral biometrics can help detect fraud and verify the identity of a user with a high degree of accuracy. Because it considers the unique ways individuals navigate and interact with digital systems, behavioral biometrics creates a highly accurate and difficult-to-replicate interaction signature. For example, if a user typically types at a certain speed and with a particular rhythm, any deviation from that pattern could indicate an imposter trying to access the system using the legitimate user's credentials.

Benefits and Limitations of Behavioral Biometrics

One of the benefits of behavioral biometrics is that it can work silently in the background without disrupting the user experience. This is because the system can analyze behavior as users interact with the system without requiring any additional input.

However, there are also some potential drawbacks to using behavioral biometrics. For example, the system may not accurately capture a user's behavior in all circumstances, such as if the user is using a different device or input method than usual. For example, if a user typically logs in to a system using a desktop computer and keyboard, but then tries to log in using a mobile device with a touchscreen, their behavior may be different, which could cause the system to flag the access attempt as suspicious. Similarly, if the user is typing in a noisy environment or using a different keyboard than usual, this could also affect their typing patterns, and potentially lead to false alarms.

Behavioral biometrics may also encounter challenges capturing a user's behavior under certain circumstances, such as high-stress levels or physical conditions affecting motor skills. For example, if the user is typing quickly because they are under a deadline or are nervous, their typing patterns may deviate from their typical behavior. Similarly, individuals with conditions like Parkinson's disease, which affect motor skills, may also pose challenges to the accuracy of the behavioral biometrics system.

Additionally, there may be concerns around privacy and data protection, as behavioral biometrics involve the collection and analysis of sensitive user data, such as keystrokes, mouse movements, and other behavioral patterns, to verify the user's identity.

Mitigating Risks

First, it's important to implement behavioral biometrics as part of a multi-factor authentication system that includes other methods, such as passwords or tokens. This can help ensure that even if the behavioral biometrics system cannot accurately capture the user's behavior in a particular situation, there are still other authentication methods in place to verify their identity. Additionally, it's important to regularly review the performance of the behavioral biometrics system and update it as needed to ensure it remains accurate and effective in detecting fraudulent activity.

Second, because behavioral biometrics data could be used to track user behavior beyond the authentication process, which could be used for targeted advertising or other purposes, it's important to implement strong security measures to protect behavioral biometrics data. This can include using encryption to protect the data in transit and at rest, limiting access to the data to only authorized personnel, and regularly monitoring the system for any signs of potential data breaches or security threats.

Another important consideration is providing transparency and control to users over how their data is collected and used. This can include providing clear and detailed information about the purpose and scope of the behavioral biometrics system, obtaining explicit consent from users to collect and use their data, and providing users with the ability to opt out of the system if they choose.

Conclusion

While behavioral biometrics can be a valuable tool for advanced authentication, it's important to implement the technology in a way that is respectful of users' privacy rights and protections. By carefully considering and addressing the privacy risks and concerns, organizations can implement a secure and effective authentication system that maintains user trust and confidence.

VikingCloud provides a range of services to help identify, assess, and minimize organizational risk - talk to an expert today.