Summary
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 ...
Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.
Read now
Unlock full access