Risk-Based Authentication in the Modern Digital Landscape
In today’s digital environments, there are no shortage of security measures being used to protect sensitive data. Zero-trust and multifactor authentication (MFA) are common strategies companies have taken to stay ahead of bad actors. Unfortunately, as security standards improve, attacker intelligence does too. To continue battling security threats, organizations can implement a risk-based authentication (RBA) strategy, which enhances security through dynamic authentication. At the same time, RBA approaches also improve user experience with minimal friction. Beyond enhanced security and better user experiences, an RBA approach also allows organizations to more easily and effectively scale and adapt to evolving risks.
Risk-Based Authentication 101: What is RBA and Why Should Companies Choose It?
Risk-based authentication is an authentication approach that evaluates risks and adapts to authentication requirements accordingly. It is designed to enhance security and promote user experience and includes analyzing different risks such as user behavior, device profiling or location details to detect anomalies or suspicious activity. For example, if a user is logging in to an account from a strange location or at an unusual time of day, this will alert the system and require additional security measures to prevent unauthorized access.
This approach is meant to strike a balance between security and positive user experience–users can securely access accounts without any hassle, with additional measures only being required in higher-risk scenarios. While traditional authentication processes (such as username/password combinations) maintain a fixed level of security, RBA takes into account various factors and assigns a risk score to each user or transaction. It then changes authentication based on the level of risk associated. For high-risk situations, like low confidence in user identity at the time of a login attempt, multi-factor authentication or security questions may be implemented. Since this approach adjusts based on risk level, the authentication process becomes streamlined and simplified for users, creating a positive experience with minimal conflict while maintaining high security.
AI is Evolving Every Industry: How AI Will Impact Your RBA Strategy
AI is a key pillar for RBA success. It enables continuous monitoring and provides advanced user analysis and real-time risk scoring, ultimately using the collected data for adaptive authentication. Adaptive authentication flags when additional authentication is needed to keep environments secure. While AI functions as a powerful tool for innovation, it can also promote adversarial attacks specifically designed to confuse RBAs and make systems vulnerable.
When these attacks occur, hackers attempt to deceive AI algorithms into making incorrect decisions or producing unexpected outputs. For instance, a threat actor may try to manipulate user behavior details to produce a low-risk score and then bypass additional security measures that might otherwise be flagged. This makes it easier to gain unauthorized access and leaves organizations unprotected.
With AI versus AI competing for access control, it’ll be essential to develop RBA strategies that are prepared for an AI-powered future. To mitigate the risk of adversarial attacks, RBA strategies need to be paired with additional techniques. Regular testing, monitoring and updating of AI models are critical to addressing emerging risks and maintaining the security of RBA systems.
The Hidden Key to RBA Success: Creating a Positive User Experience
RBA is built on the premise of removing friction for users while preserving security integrity. But with a bad user design, RBA strategies can quickly prove to be counterproductive. This is because, without positive user experiences, user satisfaction with RBA decreases and leads to chaotic and bad user behavior. If users are not properly training algorithms due to a bad user experience, the ML and AI required for effective RBA are undermined and the result is a compromised RBA system.
Instead, companies need to prioritize positive UX in RBA strategies from the start to promote user acceptance, and engagement, and build trust. This includes simplifying the process and providing clear and concise instructions for performance. Reducing unnecessary steps, eliminating complex or confusing requirements, minimizing input fields, or even just making sure organizations are using plain language during implementation are small steps companies can take to make RBA techniques more user-friendly.
With improved UX for RBA strategies, organizations can create a chain reaction of benefits. When users have improved experiences, they are more likely to trust and embrace the technique. This increased acceptance of RBA leads to better training for the required AI systems, which enables a smarter, more secure and more effective RBA approach.
The modern, digital landscape has introduced new security innovations and challenges. A risk-based authentication approach maintains security through evolving risks by leveraging AI systems. These systems then assess risk levels and implement dynamic authentication based on the level of risk detected, creating a more secure environment while streamlining user management. Pairing regular testing and updated AI models with a strong user experience are the keys to unlocking a comprehensive RBA technique.
Adopt this secure, flexible, and scalable approach for sustainable growth now.
