How do advanced detection systems identify hidden or unusual activity within network environments?
I have been reading about systems that can detect unusual or hidden activity within networks, and I am curious about how they actually work in practice. It sounds like these systems are able to monitor everything happening in the background and then highlight anything that does not match normal behavior. What I want to understand is how the system defines what is “normal” in the first place. Since every network can have different patterns depending on usage, how does the system learn and adapt to those patterns over time? Also, when something unusual is detected, does the system automatically take action or does it simply alert a human operator? I am trying to figure out how much control is given to automation versus human decision-making in these kinds of setups.