According to IBM, 20% of breaches are caused by compromised credentials. In 2021 25% of businesses have completed deployment of AI-based security, while 40% are partially deployed. Investing in AI-based security can save a business up to $3.81 million in 2021.
Biometrics technology can be split into three domains: identification, verification, and authentication. Identification is used when the system wants to know who the user is. Verification is about using that biometric information to determine if any other information is associated with the user. Finally, the goal of authentication is to understand if the identity the user claims to be is correct and authorized to access the services and data they are requesting.
One of the most important takeaways for any business considering biometric security methods is that it is not always wise to rely on only one form of biometric technology, i.e. unimodal. Instead, a multimodal approach that uses more than one type of biometrics is much more secure. It can include facial/voice recognition, iris scanning, or fingerprints authentication.
Facial recognition is one of the areas where AI and ML prove to be most helpful. Since 3D cameras can get much more information about a human face than a two-dimensional camera would, facial recognition is much more secure than before as a biometric authentication technology. Used extensively with augmented reality solutions, AI can help make facial recognition by computers much easier by analyzing facial features and matching them with a database.
To improve the accuracy and effectiveness of biometric authentication technology, it’s important to layer security with multimodal biometric recognition solutions. Evgeniy Krasnokutsky Ph.D., AI/ML Solution Architect at MobiDev, explains: “For instance, there is Nvidia Docker that can simplify the deployment of the system, while a service provider (such as AWS) can provide an uninterrupted communication channel, computing power for neural networks, and a convenient interface for scaling your system”.
By combining a microservice-based architecture, WebRTC, and machine learning-powered biometric recognition, we developed a single sign-on (SSO) biometric authentication solution for a US-based firm. Utilizing voice and facial recognition, we developed an enterprise verification as-a-service (EVaas) solution that uses the technologies discussed earlier.
This product proved that biometric authentication systems can be highly customizable and easy to use, powering a very simple user interface from behind the scenes. In addition, this example was able to integrate with existing systems via API.
More detailed information about AI biometric authentication can be found at https://mobidev.biz/blog/ai-biometrics-technology-authentication-verification-security
MobiDev is a US-based software engineering company focused on helping visionaries create their products with ease and joy. The company invests into technology research and has years of experience building AI-powered solutions, implementing machine learning, augmented reality, and IoT.