In an increasingly interconnected world, and with the progressive spread of the IoT, it becomes essential to effectively analyze network traffic in search of anomalies that can represent reliable indications of possible compromises (such as the presence of botnets).
On the other hand, the exclusive use of automated systems in performing network anomaly detection tasks exposes us to the risk of having to manage an increasing number of misleading signals (false positives).
It is, therefore, more appropriate to integrate the automated anomaly detection activities with analysis carried out by human operators, exploiting AI algorithms as filters, in order to only select the anomalies that are really worthy of in-depth attention from the analysts.
In the next chapter we will deal with AI solutions for securing user authentication.
