Associated Random Neural Networks for Collective Classification of Nodes in Botnet Attacks. (arXiv:2303.13627v1 [cs.NI])

Botnet attacks are a major threat to networked systems because of their
ability to turn the network nodes that they compromise into additional
attackers, leading to the spread of high volume attacks over long periods. The
detection of such Botnets is complicated by the fact that multiple network IP
addresses will be simultaneously compromised, so that Collective Classification
of compromised nodes, in addition to the already available traditional methods
that focus on individual nodes, can be useful. Thus this work …

addition addresses attack attackers attacks botnet botnets classification compromise compromised detection fact focus high ip addresses major network networks neural networks nodes random systems threat turn work