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RSYS_Biometric_Solution_Brief

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2 www.radisys.com RADISYS SOLUTION BRIEF | Evolve Two-Factor Authentication with In-Network Biometric Authentication Better Security Rises from Better Technologies With the increased sophistication of identity thieves, businesses are using a wide variety of techniques to keep their networks and applications safe from unauthorized access. Unscrupulous hackers use covert tactics to pry data from unsuspecting employees that ultimately enables unauthorized access and these tactics are becoming cleverer every day. These information thieves create identity profiles that use "knowledge" oriented attributes often used to create account profiles, which IT teams often use to "confirm" identities. A successful breach occurs when the hacker provides the correct responses to the challenges used for authenticating the user, allowing the fraudulent person to assume their identity, which can often lead to significant headaches, monetary loss, and private data exposure for both the employee and the business. Security systems are using new tactics to improve security and multi-factor authentication is one of these new tools. In most common two-factor authentication (2FA) systems, the valid users provide correct responses to two unique methods that confirm their identity. The methods rely on attributes like knowledge of and receipt of information: a person remembers their password and they enter a number sent by text or phone call to complete the authentication process. While more effective than a single password, this technique is inherently slow and less than fool-proof. The user must wait until they receive the text or phone call that delivers the final portion of the authentication process. Delays in communication can cause failure in the process if the text or email or call does not arrive promptly. Machine Learning (ML) and Artificial Intelligence (AI) technologies combined with more powerful and accessible computing resources, are improving the security of user authentication solutions. AI-powered computer vision and speaker verification capabilities allow authentication systems to use biometric characteristics in the user authentication process. Biometric information, which includes images of facial features or palm prints, scans of retinas, or voice samples, are unique physical attributes that uniquely identify a person. 1 The global biometric authentication and identification market is projected to grow over US$51 Billion by 2023 at a CAGR of 22.54% (2018-2023). 2 These technologies are often implemented in end-user devices or local customer premise systems, limiting their use and security for business and network-based applications. The plethora of vendors and devices outside of service provider or enterprise control means capabilities and performance will vary and control is limited. As a result, these approaches are not cost effective, scalable, or even viable in applications like banking, customer support, telehealth, and other communication applications where reliable authentication is critical. Today's Communication Service Provider (CSP) networks, which have more stringent performance level guarantees and reach closer to the user or business edge, can quickly and efficiently process speech and video streams. This enables reliable authentication services using AI-driven computer-vision and Global Biometric Authentication and Identification Market is Projected to Grow over US$51 Billion by 2023 at a CAGR of 22.54% (2018-2023) 1. https://www.grandviewresearch.com/industry-analysis/biometrics-industry 2. https://www.prnewswire.com/news-releases/global-biometric-authentication-and-identification-market-focus-on-modality- face-eye-fingerprint-palm-and-vein-motility-application-and-technology-trends-analysis-and-forecast-2018-2023-300830180.html

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