• How AI is Changing Network Access Control—And What It Means for Security

     

    Cyber threats don’t break down the door anymore—they walk right in. Stolen credentials, rogue devices, and unseen security gaps make it easier than ever for attackers to slip past defenses. IT teams try to keep up with access controls, but with more devices, users, and remote connections than ever, the old ways of securing a network fall short.

    The problem isn’t that businesses lack security tools—it’s that traditional access control wasn’t built for the scale and complexity of modern networks. Artificial intelligence is changing that. With the ability to analyze patterns, detect anomalies, and make split-second decisions, AI is helping IT teams stay ahead of threats that would otherwise go unnoticed.

    AI’s Role in Network Access Control

    AI makes access control faster and smarter. While traditional security systems rely on static rules—like usernames, passwords, and predefined permissions—AI adapts in real time, adjusting security based on user behavior, device activity, and changing risk levels.

    Here’s what AI brings to the table:

    • Identifies and classifies devices automatically: AI-powered recognition ensures that every device—whether it’s a personal phone, IoT sensor, or guest laptop—gets the right level of access without manual intervention.
    • Instantly spots suspicious activity: AI monitors login attempts, device behavior, and network traffic. If an employee suddenly logs in from an unusual location or a device behaves abnormally, AI flags the activity and triggers security protocols.
    • Adjusts access based on context: Instead of blocking legitimate users or letting in potential threats, AI evaluates risk dynamically. If a known employee logs in from an unrecognized device, AI might prompt multi-factor authentication rather than deny access outright.
    • Dynamically enforces security policies: AI updates security rules based on real-time network activity. If new risks emerge, AI modifies access permissions immediately, keeping threats out without causing unnecessary disruptions.

    Best Practices for Implementing AI

    AI is reshaping how access decisions are made—but putting it to work effectively takes more than flipping a switch.

    Here are some key considerations to keep in mind:

    • Maintain control of automation: While AI can automate your security decisions, your IT team still needs visibility and oversight. Choose solutions that let admins review AI-driven actions and adjust policies as needed.
    • Integrate with existing security tools: Access control powered by AI works best when it fits cleanly into your existing setup. Look for options that work seamlessly with your identity platforms, monitoring tools, and endpoint security—without adding extra complexity.
    • Train it with quality data inputs: AI learns from what’s happening on your network, but how well it adapts depends on the data feeding it. Make sure your systems are capturing accurate, relevant activity, so AI can keep up with shifting threats.
    • Balance security with usability: Security should be strong, but not at the cost of usability. Use tools that minimize unnecessary prompts or delays for trusted users while still responding to risky behavior when it appears.

    AI is changing how we think about network access control. With Aruba ClearPass, a network access control solution that uses AI to identify devices, enforce policies, and adapt to risk in real time, Zunesis can help you stay ahead of threats, streamline access, and protect every device on your network

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