Machine learning and AI in cybersecurity give you back control by learning what “normal” looks like across your network, then flagging what actually deserves your attention. Instead of chasing every blinking alert, you start seeing which signals are quiet but…
Behavior-based SIEM turns noisy alerts into real signals by teaching your system what “normal” looks like in your environment. Instead of flooding your team with every rule match, it learns patterns of users, devices, and applications, then highlights what truly…
UEBA and NBA solve two different problems: UEBA helps you understand risky users and devices, while NBA helps you understand risky network traffic. When an alert pops up, UEBA asks, “Who is doing this, and is it normal for them?”…
Profiling network device behavior means teaching your system what “normal” looks like for every device, then spotting even small changes. When a quiet printer suddenly sends gigabytes of data overseas, or a camera starts talking on a strange port, that…
AI-driven behavioral analysis is the shift from waiting for an attack to stopping it before it happens. It uses machine learning to understand the normal rhythm of your digital environment, from user logins to data transfers. When something acts out…
Your behavior is the most powerful security tool your network has. Not the password, not the token, you. Behavioral biometrics in network security tracks the quiet patterns you don’t even notice, your typing rhythm, how you move your mouse, the…
Detecting C2 communication means spotting a quiet, unnatural pattern hiding inside normal network noise. It’s the steady, almost polite check-in from a compromised host to its controller, buried under real user traffic and routine system calls. You might not catch…
An attacker already inside your network is like a burglar who’s slipped past the front door and now walks your hallways. They move slowly, testing doors, probing access, hunting for the “safe” where real value lives. That quiet wandering, from…
You detect anomalous endpoint behavior by teaching a machine what normal looks like, then watching for the slightest deviation. It’s not about known viruses, it’s about spotting the weird. The process that spawns from a temp folder, the sudden spike…
You can’t defend what you don’t understand, and that starts with knowing what “normal” looks like in your own environment. When you map everyday user behavior, the logins, access patterns, data usage, you turn random events into a baseline you…